0

Actuation and Control Applications

2010;():1-6. doi:10.1115/DSCC2010-4002.

Aiming at studying the impact of steady-state flow force to YL-56 load sensing pump and how to reduce the effects of flow force on control valve spool, the factors of steady-state flow force were analyzed using CFD software FLUENT, and virtual prototype of load sensing pump was developed to study its characteristics. Compared with the effect of using position-controlled proportional solenoid to drive the throttle valve in simulation, the use of force-controlled proportional solenoid could suppress the impact of steady-state flow force much better, and the problem that the output flow increased when load pressure rose was solved. The experiment test results indicate that using force-controlled proportional solenoid in throttle valve can decrease the impact of steady-state flow force quite well.

Commentary by Dr. Valentin Fuster
2010;():7-14. doi:10.1115/DSCC2010-4088.

There are appreciable losses in crop output at all the stages in grain production like harvesting, transportation, storage, etc. To reduce grain loss during the harvesting process, it is desirable to effectively control the header height of the combine harvester. The desired header height control is able to follow the shape of the terrain and reject disturbances from the ground. This paper presents an optimal state feedback LQR controller to achieve the control objectives. By properly defining the states and choosing the cost function, the full state feedback controller is shown to accomplish the control goals. Then a reduced states feedback controller, which uses a skyhook damper in the controller, is used to simplify the full state feedback controller. Simulation results show that with less feedback information, the reduced order state feedback controller preserves the ability to achieve good reference tracking and disturbance rejection.

Commentary by Dr. Valentin Fuster
2010;():15-19. doi:10.1115/DSCC2010-4116.

Magnetorheological fluids are often proposed for applications requiring fast response and good controllability but the dynamic characteristics of the MR devices are seldom analyzed in detail. The aim of this study is to present a magnetorheological valve optimized for fast dynamical response. The fundamental design criteria for fast MR valves are discussed and an experimental valve designed for high frequency actuation is analyzed. It is shown the performance figures generally reported for MR technology can be significantly improved. The results show a step pressure difference of 7 MPa can be controlled with a response time of 0.7 ms. The maximum rate of change for controllable pressure was measured to achieve 20.2 MPa in one millisecond.

Commentary by Dr. Valentin Fuster
2010;():21-28. doi:10.1115/DSCC2010-4140.

In this article, a mechatronic system to compensate for the effect of hardware dynamics and achieve rapid resonance identification for an ultrasonic-vibration-assisted microforming system is developed. Recently, micromachining technology, including microforming, microjoining, and micropunching, has attracted great interests due to the need of miniaturized manufacturing system in emerging applications. It has been demonstrated that significant benefits such as reduction of input energy and prolongation of tool life can be gained by introducing ultrasonic vibration into the micromachining process, particularly when the vibration is maintained at the resonant frequency of the vibrating workpiece. However, the fundamental mechanism of ultrasonic vibration effect during the micromachining process has not yet been understood; the electrical actuators currently used to generate the ultrasonic vibration are bulky and not suitable for miniaturization of the micromachining system; and the control of ultrasonic vibration is primitive and far from being optimal. Motivated by these challenges, a microforming platform based on magnetostrictive actuator has been developed recently. Based on this microforming experiment platform, the main contributions of this article are two folds: (1) the use of a novel iterative learning control technique along with a vibration oscillation regulation circuit to compensate for the effect of the magnetostrictive actuator dynamics on the ultrasonic vibration generation, and thereby maintain the same vibration amplitude across a large excitation frequency range, and (2) the use of the Fibonacci search algorithm to achieve rapid online identification of the resonant frequency. Experimental results obtained from the developed magnetostrictive-based microforming platform are presented and discussed to demonstrate the proposed approach.

Commentary by Dr. Valentin Fuster
2010;():29-36. doi:10.1115/DSCC2010-4145.

This paper presents an approach for using two-port circuit synthesis methods as a basis for designing actuator subsystems. The development of this methodology is generally motivated by problems in retrofit design, where technology reinsertion is required to replace legacy systems, or for early stage design in new mechatronic systems. The particular problem of electric ship control surface actuation is used as an example application. A procedure that integrates two-port network synthesis methods with a model-basis conveyed using bond graphs is presented and applied to the problem of synthesizing a candidate actuation system for a submarine control surface. Studying the control surface actuator problem shows that a synthesis method is capable of providing insight into balancing passive compensation with actuation (active elements). The ability to partition active and passive system elements suggests promise in developing a means for integrating passive energy storage with actuation subsystems.

Topics: Design , Ships
Commentary by Dr. Valentin Fuster

Advanced Automotive Powertrain Control

2010;():37-44. doi:10.1115/DSCC2010-4012.

This paper presents a new control allocation (CA) scheme for improving operational energy-efficiency of over-actuated systems. By explicitly incorporating actuator efficiency functions into the CA formulation, minimum power consumption is achieved while distributing the desired virtual control among the redundant actuators. For some physical systems (e.g. hybrid electric or pure electric vehicles with electric motors) whose actuators have dual actuation modes (e.g. driving or regenerative braking of electric motors) that possess different efficiencies and/or energy consuming or gaining characteristics, a virtual actuator method is devised to augment the systems for the energy-efficient CA scheme. An electric vehicle model with rear/front axle motors or four in-wheel / hub motors constructed in the full-vehicle CarSim® simulation package is used as an application case study to show the effectiveness of the proposed energy-efficient CA method.

Commentary by Dr. Valentin Fuster
2010;():45-52. doi:10.1115/DSCC2010-4049.

This paper describes the development and experimental validation of a control-oriented, real-time-capable, Diesel engine instantaneous fuel consumption and brake torque model under warmed-up conditions. Such a model, with the capability of reliably and computationally-efficiently estimating the aforementioned variables at steady-state and transient engine operating conditions, can be utilized in the context of real-time control and optimization of hybrid powertrains. The only two inputs of the model are the torque request and the engine speed. While Diesel engine dynamics are highly nonlinear and very complex, by considering the Diesel engine and its control system (engine control unit (ECU)) together as an entity, it becomes possible to predict the engine instantaneous fuel consumption and torque based on only the two inputs. A synergy between different modeling methodologies including physically-based grey-box and data-driven black-box approaches were integrated in the Diesel engine model. The fueling and torque predictions have been validated by means of FTP72 test cycle experimental data from a medium-duty Diesel engine at steady-state and transient operations.

Commentary by Dr. Valentin Fuster
2010;():53-60. doi:10.1115/DSCC2010-4149.

Camless valve actuation systems, also referred to as Fully Flexible Valve Actuation systems, use electronically controlled actuators to replace the camshaft in an internal combustion engine. This paper presents the control design for such an actuation system to enable the precise valve motion control during engine speed transients. The desired valve motion (reference) remains periodic in the crank angle domain, but becomes cyclic and aperiodic in the time domain when the engine speed changes in real-time. This phenomenon motivates the control design in the rotational angle domain. However, this approach results in a time-varying model for the plant. A systematic method for obtaining the discrete time-varying Input/Output representation of higher order systems is developed to enable the application of the newly developed time-varying repetitive control to plants with complex dynamics. The use of a variable sampling rate helps accurately represent complex reference signals using low dimensional models. The implementation of the simulations on a rapid control prototyping system helps identify and address potential issues that influence the controller execution time which directly affects the maximum engine speed at which it can be used.

Commentary by Dr. Valentin Fuster
2010;():61-68. doi:10.1115/DSCC2010-4171.

With its superior power to weight ratio, the hydrostatic dynamometer is an ideal candidate for transient engine or powertrain testing. Given its high bandwidth, the hydrostatic dynamometer can be further used as a virtual power source to emulate the dynamics of the automotive hybrid power sources. This will greatly expedite the investigation of various hybrid powertrain architectures and control methodologies without building the complete hybrid system. This paper presents the design, modeling, nonlinear tracking control and experimental investigation of a transient hydrostatic dynamometer. An electronically controlled load sensing mechanism is employed to facilitate the supply pressure control, and a two-stage high bandwidth valve is used as the primary actuator for the loading pressure control. To enable the model-based control, a 9th order physics-based model is formulated and then, identified and validated with experimental data. On this basis, model-based nonlinear tracking controls are designed for this multivariable nonlinear system to realize the precise engine speed tracking. A nonlinear model-based inversion plus PID control is first implemented and then, a state feedback control via feedback linearization is designed for reference tracking. Experimental results demonstrate precise tracking performance with less than 5% tracking error for both transient and steady state operations.

Commentary by Dr. Valentin Fuster
2010;():69-75. doi:10.1115/DSCC2010-4184.

A torque converter clutch (TCC) is an important element of automatic transmissions because it affects fuel economy and driveability. Although torque converters are ideal launch devices for transmissions, they are inefficient in steady-state operations. For that reason, a TCC is used to control and minimize the slip between the torque converter pump and turbine, thereby increasing the efficiency of the driveline and improving fuel economy. However, low TCC slip speeds increase the likelihood that disturbances cause the TCC to have zero slip or crash. In the absence of TCC slip, it is essential to quickly restore slip and regain driveline isolation to maintain driveability. To recover TCC slip, pressure to the TCC must be reduced significantly to overcome the effects of clutch material nonlinearities and hydraulic hysteresis. Unfortunately, large pressure reductions can also result in undesirable slip overshoot. In this investigation, the truncated sequential probability ratio test is used to achieve fast and robust detection at the low signal-to-noise ratios caused by the low TCC slip speeds. In the event of a crash, two unique TCC pressure command sequences are presented which maximize the response of the system hydraulics while also minimizing clutch slip overshoot. The effectiveness of the proposed methods are evaluated using experimental results from small and large vehicles equipped with automatic front and rear-wheel drive transmissions.

Commentary by Dr. Valentin Fuster
2010;():77-84. doi:10.1115/DSCC2010-4189.

Internal model based repetitive control for linear time invariant (LTI) system has been widely applied to track or reject periodic signals with only the period known. It is well understood that the discrete generating dynamics of the periodic signal can be obtained by finite sampling, and embedding it as the internal model will yield asymptotic performance. However, the traditional repetitive control framework will no longer work for periodic signals with varying peak to peak amplitude. As will be revealed in this paper, the generating dynamics of this kind of signals is time varying, and thus simply embedding its generating dynamics as the internal model will no longer ensure asymptotic performance. The necessity of investigating tracking or rejecting varying magnitude periodic signals comes from a wide class of anticipated applications, one example of which is the hybrid vehicle powetrain vibration reduction. In the hybrid vehicles, engine starting and stopping occur frequently to switch between power sources, which could cause driveline vibration. With proper formulation, the oscillation signal becomes periodic with varying magnitude. To suppress such vibration, in this paper, the generating dynamics of this unique signal is first derived, and then its corresponding controller design method is presented. After a series of simulations and case studies, the proposed control framework is demonstrated to be a promising solution for the hybrid powertrain vibration reduction problem.

Commentary by Dr. Valentin Fuster

Advanced Engine Dynamics and Control

2010;():85-92. doi:10.1115/DSCC2010-4045.

This paper presents an observer design for Diesel engine aftertreatment system NO and NO2 concentrations estimations. NO and NO2 have different reaction characteristics within SCR systems. Current production NOx sensors cannot differentiate NO and NO2 . Such an observer thus can be used by selective catalytic reduction (SCR) system control and diagnosis purposes. Diesel oxidation catalyst (DOC) and Diesel particulate filter (DPF) were considered as the catalysts which can affect NO/NO2 fraction of the exhaust gas upstream of the SCR. The observer was designed based on an experimentally-validated control-oriented dynamic model which can accurately represent the NO and NO2 dynamics from engine-out, through DOC, and to DPF. Stability of the observer was theoretically proved through a Lyapunov analysis assisted by insight into the system characteristics. The effectiveness of the observer was shown by comparing the estimated NO and NO2 concentrations with the measured ones by a Horiba emissions measurement system.

Topics: Diesel engines
Commentary by Dr. Valentin Fuster
2010;():93-99. doi:10.1115/DSCC2010-4053.

Proposed in this paper is an automated framework for calibration of diesel engine governors. The process involves two basic parts, online engine model identification followed by governor gain design. A previously developed Instrumental Variable 3 Step Algorithm for closed loop system identification is used to estimate the engine model. The identified model is then used in two different governor calibration approaches. The first approach employs a typical governor structure involving acceleration feedback. It will be shown that this governor structure reduces to a classical two degree-of-freedom design. The second approach is based on a procedure in which a desired open-loop transfer function (target transfer function) is shaped such that the same performance specifications as for the first design are satisfied. The control design methods are applied for an off-highway diesel engine with a disengaged transmission. In-field data collected from the engine operating closed-loop is used to identify a model for the open-loop system and the controller gains are then determined. The loop shaping method is then applied to the identified model to design a feedback controller and a prefilter. The efficacy of both loops in terms of tracking performance and noise rejection has been demonstrated through a time domain simulation of both closed-loop step responses.

Topics: Diesel engines
Commentary by Dr. Valentin Fuster
2010;():101-107. doi:10.1115/DSCC2010-4143.

Due to the need for clean and efficient automobile propulsion systems, this paper models an important process in the enabling of homogeneous charge compression ignition (HCCI) engines. The need for a deep understanding of charge-residual mixing in residual-affected HCCI engines requires a model of the chemical composition during the mixing process. In this paper, a chemical composition model is developed specifically for a two-zone mixing model to account for important phenomena such as the presence of unburned fuel in the residual exhaust gas. The model is developed as a control-oriented model that can be used for real-time decision making and control. This paper develops the composition model for the major species present, and also presents the method that would be used to include other minor species. The model is simulated for variations in residual gas fraction equivalence ratio, a misfire situation, and its effects on air/fuel ratio.

Commentary by Dr. Valentin Fuster
2010;():109-116. doi:10.1115/DSCC2010-4154.

A combination of a low-pressure EGR and a high-pressure EGR for Diesel engines can effectively reduce the NOx emissions. In comparison to a conventional high-pressure EGR, the combination with a low-pressure EGR introduces an additional degree of freedom for the air path control. From control perspective the weaker couplings with the charging pressure and the dynamics of the gas composition in the intake and exhaust system are the major differences between the low-pressure and the high-pressure EGR. The lower gas temperature of the low-pressure EGR further reduces the emissions. A control oriented model is presented to control the gas composition in the intake system. Therefore a reference value transformation converts a desired air mass flow rate into a desired gas composition in the intake system. Depending on the dynamical gas compositions in the intake and exhaust system, the reference value of the desired gas composition results in a setpoint for a high-pressure EGR mass flow rate controller. Due to the faster dynamics of the high-pressure EGR, this controller accounts for the fast dynamical effects in the gas system. The presented control structure in combination with the reference value generation is invariant to model and sensor uncertainties and results stationary in an air mass flow rate control. As additional control variable, the intake temperature is controlled by the low-pressure EGR mass flow rate. A calibrated desired temperature delivers the setpoint for a low-pressure EGR mass flow rate controller.

Commentary by Dr. Valentin Fuster
2010;():117-124. doi:10.1115/DSCC2010-4267.

This paper describes the modeling of a two-stroke dual chamber free piston engine (FPE) running homogeneous charge compression ignition (HCCI) combustion with an embedded linear alternator and a hydraulic pump. Variable compression ratio of FPE enables multi-fuel operation. Furthermore, the addition of an electric generator and hydraulic pump ensure the engine to have both high energy density and power density. These three concepts combined, will make for a highly efficient and flexible approach for engine operation. However, the characteristic of FPE also brings challenges in engine control. We propose a control oriented model that provides detailed gas exchange processes between intake/exhaust and cylinder volume, and the dynamic interactions between combustion, the linear alternator and the hydraulic pump. Influences of fuel and valve timing on engine performance are studied. Simulated engine dynamics are observed to have significant differences from conventional internal combustion engines.

Commentary by Dr. Valentin Fuster

Advanced Vehicle Dynamics and Safety Control

2010;():125-132. doi:10.1115/DSCC2010-4032.

We present a dynamic stability and agility study of a pendulum-turn aggressive vehicle maneuver. Instead of optimizing the controlled inputs to mimic the human performance profile during a pendulum-turn agile maneuver, we focus on studying the stability regions and agility performance of the vehicle motion using professional racing car driver testing data. A hybrid physical/dynamic tire/road friction model is used to capture the dynamic friction force characteristics in analysis and simulation and to compare with testing data. We also introduce the use of vehicle lateral jerk information as the agility metric to compare vehicle maneuvering performance. The analysis and testing results show that during the pendulum-turn maneuvers, the professional driver operates the vehicle outside the stable regions of the vehicle dynamics to achieve superior agility performance than that under a typical human driver model. Comparison results with a typical human driver model also show that the racing car driver outperforms in both the traveling time and the newly defined agility metric. Designing a control strategy for autonomous pendulum-turn-like safe vehicle agile maneuvers is ongoing work.

Commentary by Dr. Valentin Fuster
2010;():133-140. doi:10.1115/DSCC2010-4050.

This paper presents an in-wheel motor fault diagnosis method for fault-tolerant control of four-wheel independently driven (4WID) electric vehicles. 4WID electric vehicle is one of the promising architectures for electric ground vehicles. While such a vehicle architecture greatly increases the flexibility for vehicle control, it also raises the requirements on system reliability, safety, and fault tolerance due to the increased number of actuators. A fault diagnosis approach for finding the faulty in-wheel motor/motor driver pair is developed. The proposed diagnosis approach does not need a precise knowledge on tire-road friction coefficient (TRFC). Robustness analysis shows that the approach can work well in the presence of tire modeling errors. Simulations using a high-fidelity, CarSim, full-vehicle model indicated the effectiveness of the proposed in-wheel motor/motor driver fault diagnosis approach.

Commentary by Dr. Valentin Fuster
2010;():141-148. doi:10.1115/DSCC2010-4096.

This paper presents a method for semi-autonomous hazard avoidance in the presence of unknown moving obstacles and unpredictable driver inputs. This method iteratively predicts the motion and anticipated intersection of the host vehicle with both static and dynamic hazards and excludes projected collision states from a traversable corridor. A model predictive controller iteratively replans a stability-optimal trajectory through the navigable region of the environment while a threat assessor and semi-autonomous control law modulate driver and controller inputs to maintain stability, preserve controllability, and ensure safe hazard avoidance. The efficacy of this approach is demonstrated through both simulated and experimental results using a semi-autonomously controlled Jaguar S-Type.

Topics: Vehicles
Commentary by Dr. Valentin Fuster
2010;():149-156. doi:10.1115/DSCC2010-4144.

Stability control systems on the market today, while effective, operate without full information on the vehicle states and road friction properties. This paper presents a vehicle control scheme that takes into account vehicle state information on sideslip angle and yaw rate, as well as road coefficient of friction, to keep the vehicle within a safe region of the state space. The controller limits state growth outside of the safe area to a sliding surface defined by the distance to the closest operating point in the safe region. Experimental results validate a simple version of the controller on a low friction surface. The controller successfully stabilizes the vehicle using steer-by-wire as a control input.

Topics: Vehicles
Commentary by Dr. Valentin Fuster
2010;():157-164. doi:10.1115/DSCC2010-4168.

Given the increase in computing power over the last decade, model predictive control has received renewed attention as a technique for accomplishing high-level vehicle control. However, tire nonlinearities present a challenge for rapidly solving the optimization problem required to do model predictive control. This paper presents an approach which extracts the tire nonlinearities outside the MPC optimization, leaving a convex problem that can be solved rapidly and with guaranteed optimality. Experimental results are presented from an MPC controller using this technique that demonstrate the controller’s ability to handle tire nonlinearities during highly dynamic manuevers that saturate the tires and induce lateral-longitudinal force coupling effects.

Commentary by Dr. Valentin Fuster
2010;():165-172. doi:10.1115/DSCC2010-4250.

Wheel torque control and active front steer are effective means of improving vehicle handling and stability. In this paper, a vehicle chassis control system that controls both wheel torques at each wheel and front steer has been developed using model predictive control in order to enhance vehicle yaw motion and ability to track the desired trajectory. A simplified nonlinear tire model that is computationally efficient and easy to implement in the control algorithms and an 8 degree of freedom (DOF) vehicle model are used in the controller. The performance of this controller is compared to that based on well known Magic Formula tire model. The effectiveness and limitations of the proposed controller are discussed through simulation.

Commentary by Dr. Valentin Fuster

Aerospace and Flight Control

2010;():173-180. doi:10.1115/DSCC2010-4016.

A planar linearized interception problem of a maneuverable target is considered. A novel continuous interception strategy, based on the super-twisting second-order sliding mode control, is constructed. The sufficient conditions guaranteeing that this strategy has the maximal capture zone are established. Simulation results demonstrate that the control expenditure of the new strategy is reduced without deteriorating the homing performance in comparison with a bang-bang strategy.

Commentary by Dr. Valentin Fuster
2010;():181-188. doi:10.1115/DSCC2010-4079.

This paper presents a dynamic model for a smooth wheel travelling through loose sandy soil. Many models that are used for such wheel-soil interactions are typically static or quasi-static models. The new model builds upon these widely-used models by adding the dynamic effect of the soil deformation. The new model is validated using experiments that were carried on a new single wheel testbed which was constructed at Dalhousie University. During experiments with a smooth wheel it was noticed that the track of the wheel had repeatable ridges. Moreover, it was noticed that the corresponding torque and force data also had oscillations in it with the periods of the harmonic coinciding with the ridges in the sand left by the track of the wheel.

Topics: Modeling , Wheels
Commentary by Dr. Valentin Fuster
2010;():189-196. doi:10.1115/DSCC2010-4109.

A new approach to the attitude control of an over actuated satellite is presented. A control moment gyroscopes cluster containing four actuators in a pyramid mounting configuration, and a set of three orthogonal magnetic torque rods are considered to steer the satellite. Two steering algorithms, Moore-Penrose pseudo inverse, and the recently developed blended-inverse, are considered. The success of the blended-inverse algorithm to select the desired actuators in the system is demonstrated. It is also shown through simulations that the blended-inverse algorithm successfully carries out the maneuver without getting trapped in singular configurations, while the classical Moore-Penrose pseudo inverse algorithm fails to realize.

Topics: Torque , Rods , Satellites
Commentary by Dr. Valentin Fuster
2010;():197-206. doi:10.1115/DSCC2010-4234.

Using a dynamically scaled robotic wing, we studied the aerodynamic torque generation of flapping wings during roll, pitch, and yaw rotations of the stroke plane. The total torque generated by a wing pair with symmetrical motions was previously known as flapping counter-torques (FCTs). For all three types of rotation, stroke-averaged FCTs act opposite to the directions of rotation and are collinear with the rotational axes. Experimental results indicate that the magnitude of FCTs is linearly dependent on both the flapping frequency and the angular velocity. We also compared the results with predictions by a mathematical model based on quasi-steady analyses, where we show that FCTs can be described through consideration of the asymmetries of wing velocity and the effective angle of attack caused by each type of rotation. For roll and yaw rotations, our model provided close estimations of the measured values. However, for pitch rotation the model tends to underestimate the magnitude of FCT, which might result from the effect of the neglected aerodynamics, especially the wake capture. Similar to the FCT, which is induced by body rotation, we further provide a mathematical model for the counter force induced by body translation, which is termed as flapping counter-force (FCF). Based on the FCT and FCF models, we are able to provide analytical estimations of stability derivatives and to study the flight dynamics at hovering. Using fruit fly (Drosophila) morphological data, we calculated the system matrix of the linearized flight dynamics. Similar to previous studies, the longitudinal dynamics consist of two stable subsidence modes with fast and slow time constants, as well as an unstable oscillatory mode. The longitudinal instability is mainly caused by the FCF induced by an initial forward/backward velocity, which imparts a pitch torque to the same direction of initial pitch velocity. Similarly, the lateral dynamics also consist of two stable subsidence modes and an unstable oscillatory mode. The lateral instability is mainly caused by the FCF induced by an initial lateral velocity, which imparts a roll torque to the same direction of initial roll velocity. In summary, our models provide the first analytical approximation of the six-degree-of-freedom flight dynamics, which is important in both studying the control strategies of the flying insects and designing the controller of the future flapping-wing micro air vehicles (MAVs).

Commentary by Dr. Valentin Fuster
2010;():207-214. doi:10.1115/DSCC2010-4279.

In recent years, Sum–Of–Squares (SOS) method has attracted increasing interest as a new approach for stability analysis and controller design of nonlinear dynamic systems. This paper utilizes SOS method to design a robust nonlinear controller for longitudinal dynamics of a hypersonic aircraft model. Specifically, the searching of the nonlinear robust controller is reformulated as a robust SOS/robust LMI problem, and then solved via a stochastic iterative algorithm. As the simulation results show, the designed controller is capable of stabilizing the aircraft and following pilot commands in presence of parametric uncertainties in the aircraft model.

Topics: Design , Aircraft
Commentary by Dr. Valentin Fuster
2010;():215-223. doi:10.1115/DSCC2010-4289.

This article outlines a new control approach for flapping-wing micro-aerial vehicles (MAVs), inspired both by biological systems and by the need for lightweight actuation and control solutions. In our approach, the aerodynamic forces required for agile motions are achieved indirectly, by modifying passive impedance properties that couple motion of the power stroke to the angle of attack (AoA) of the wing. This strategy is theoretically appealing because it can exploit an invariant, cyclical power stroke, for efficiency, and because an impedance-adjusting strategy should also require lower bandwidth, weight, and power than direct, intra-wingbeat control of AoA. We examine the theoretical range of control torques and forces that can be achieved using this method and conclude that it is a plausible method of control. Our results demonstrate the potential of a passive dynamic design and control approach in reducing mechanical complexity, weight and power consumption of an MAV while achieving the aerodynamic forces required for the types of high-fidelity maneuvers that drive current interest in autonomous, flapping-wing robotics.

Topics: Vehicles , Wings
Commentary by Dr. Valentin Fuster

Autonomous Systems

2010;():225-232. doi:10.1115/DSCC2010-4076.

The simplest strategy for extremum seeking-based source localization, for sources with unknown spatial distributions and nonholonomic unicycle vehicles without position measurement, employs a constant positive forward speed. Steering of the vehicle in the plane is performed using only the variation of the angular velocity. While keeping the forward speed constant is a reasonable strategy motivated by implementation with aerial vehicles, it leads to complexities in the asymptotic behavior of the vehicle, since the vehicle cannot settle—at best it can converge to a small-size attractor around the source. In this paper we regulate the forward velocity, with the intent of bringing the vehicle to a stop, or as close to a stop as possible. The vehicle speed is controlled using simple derivative-like feedback of the sensor measurement (the derivative is approximated with a washout filter) to which a speed bias parameter Vc is added. The angular velocity is tuned using standard extremum seeking. We prove two results. For Vc in a certain range around zero, we show that the vehicle converges to a ring around the source and on average the limit of the vehicle’s heading is either directly away or towards the source. For other values of Vc > 0, the vehicle converges to a ring around the source and it revolves around the source. Interestingly, the average heading of this revolution around the source is more outward than inward—this is possible because the vehicle’s speed is not constant, it is lower during the outward steering intervals and higher during the inward steering intervals. The theoretical results are illustrated with simulations.

Commentary by Dr. Valentin Fuster
2010;():233-240. doi:10.1115/DSCC2010-4113.

A new method of path planning and tracking while maintaining a constant distance from underwater moving objects has been developed for autonomous underwater vehicles (AUVs). First a kinematics controller that generates the proper trajectories is designed. Then a dynamics sliding mode controller is employed to drive the vehicle on the desired trajectories. The dynamics controller is robust against the parameter uncertainty in the dynamics model of the vehicle. Results of numerical simulations for INFANTE-AUV model show excellent performance for tracking of an object on sinusoidal trajectory.

Commentary by Dr. Valentin Fuster
2010;():241-248. doi:10.1115/DSCC2010-4142.

This paper presents a Statistical Mechanics-inspired navigation algorithm with dynamic adaptation and complete coverage of unknown environments, which is built upon the concept of generalized Ising model. The algorithm enables autonomous vehicles to cover all areas in the environment, avoid unknown obstacles and adapt to target neighborhoods. Potential applications of this algorithm are humanitarian de-mining, hazard detection and floor-cleaning tasks. The algorithm has been validated on a Player/Stage simulator with an example of minesweeping.

Topics: Vehicles , Navigation
Commentary by Dr. Valentin Fuster
2010;():249-256. doi:10.1115/DSCC2010-4188.

The concept of velocity occupancy space was developed in order to facilitate a vehicle in avoiding moving and stationary obstacles and navigating efficiently to a goal using only uncertain sensor data. However, the original velocity occupancy space concept was designed for holonomic vehicles that are capable of instantaneous velocity changes — capabilities that are not possessed by most actual vehicles. This paper presents two methods by which velocity occupancy space can be adapted to work within the kinodynamic constraints of a differential drive vehicle, a common configuration for experimental robots, with bounded acceleration capabilities. These two different adaptations of the velocity occupancy space concept are proposed and evaluated in light of their respective suitability under different vehicle conditions.

Topics: Vehicles
Commentary by Dr. Valentin Fuster
2010;():257-264. doi:10.1115/DSCC2010-4254.

This paper presents a comparison between the centralized and de-centralized controllers of a magnetically levitated vehicle. The simulation accounts for the interaction between the vehicle and girder through the control electromagnetic levitation force of the vehicle. In this way, the effects of: controller dynamics, electrodynamics, vehicle dynamics, and vehicle velocity are considered in order to provide a more realistic simulation. The main purpose of this work is to qualify the performance of each controller in sustaining an acceptable ride quality referred to ISO2631.

Commentary by Dr. Valentin Fuster
2010;():265-272. doi:10.1115/DSCC2010-4263.

Two frameworks based on Model Predictive Control (MPC) for obstacle avoidance with autonomous vehicles are presented. A given trajectory represents the driver intent. An MPC has to safely avoid obstacles on the road while trying to track the desired trajectory by controlling front steering angle and differential braking. We present two different approaches to this problem. The first approach solves a single nonlinear MPC problem. The second approach uses a hierarchical scheme. At the high-level, a trajectory is computed on-line, in a receding horizon fashion, based on a simplified point-mass vehicle model in order to avoid an obstacle. At the low-level an MPC controller computes the vehicle inputs in order to best follow the high level trajectory based on a nonlinear vehicle model. This article presents the design and comparison of both approaches, the method for implementing them, and successful experimental results on icy roads.

Commentary by Dr. Valentin Fuster

Biological Systems

2010;():273-280. doi:10.1115/DSCC2010-4013.

We present a new, two-pool, linear, time-varying model to describe the short term dynamics of the Ca-PTH axis. We use an asymmetrical reverse sigmoid PTH secretion rate function in the model. This results in an asymmetrical reverse sigmoid relationship between plasma Ca++ and plasma parathyroid hormone (PTH) concentrations (Ca-PTH relationship). In the first validation of this kind, with parameters estimated separately based on each subject’s hypocalcemic clamp test data, we successfully test the model’s ability to predict the same subject’s induced hypercalcemic clamp test responses. We then show that the conventional symmetrical reverse sigmoid Ca-PTH relationship is deficient.

Commentary by Dr. Valentin Fuster
2010;():281-288. doi:10.1115/DSCC2010-4017.

ICSI (Intra-Cytoplasmic Sperm Injection) has attracted research interest from both biological and engineering groups. This technique is used to create genetically identical offsprings of many different species (mice, rats, cattle et al.). We focus on a relatively recent technology for ICSI, called Ros-Drill© (Rotationally Oscillating Drill). In this paper, we present a procedure to automate a critical part of the ICSI operation: initiation of the rotational oscillation phase. (The visual feedback is on the real-time visual monitoring of the tip of the injection pipette. First, the real-time feature extraction in visual feedback is explained). The proposed algorithm which does this is split up into two parts: off-line and on-line. In the off-line part a proper thresholding grey level is determined. In the on-line part a realtime algorithm tracks the tip of the injecting pipette. A predetermined, species-specific penetration depth is used to initiate the rotational oscillation action of the drill. This real-time visual feedback control is compared with an earlier curvature-based analysis. Algorithmic stages as well as the outcomes from the concept validation tests are presented.

Commentary by Dr. Valentin Fuster
2010;():289-296. doi:10.1115/DSCC2010-4060.

Insulin pumps and continuous glucose monitors enable automatic control of blood glucose (BG) levels for patients with type 1 diabetes. Such controllers should carefully assess the likely future BG levels before injecting insulin, since the effects of insulin are prolonged, potentially deadly, and irreversible. Meals pose a strong challenge to this assessment as they create large, fast disturbances. Fortunately, meals have consistent and predictable effects, if their size and start time are known. We present a predictive algorithm that embeds meal detection and estimation into BG prediction. It uses a multiple hypothesis fault detector to identify meal occurrences, and linear Kalman filters to estimate meal sizes. It extrapolates and combines the state and state covariance estimates to form a prediction of BG values and uncertainties. These inputs enable controllers to assess and trade off the acute risks of low and chronic risks of high BG levels. We evaluate the predictor on simulated and clinical data.

Topics: Blood , Diabetes
Commentary by Dr. Valentin Fuster
2010;():297-303. doi:10.1115/DSCC2010-4230.

We consider two and three phase-oscillators as in the Kuramoto model of coupled oscillators, replacing the sine wave interaction with a sawtooth wave. We show that for the case of non-uniform input-symmetric coupling strengths, the non-smooth, piecewise-linear dynamics synchronizes when the coupling strengths are large enough to overcome the differences in the natural frequencies of the oscillators. Stability is analyzed separately in the regions where the dynamics is linearized. These regions are separated by the switching boundaries where the vector field is discontinuous.

Commentary by Dr. Valentin Fuster
2010;():305-312. doi:10.1115/DSCC2010-4276.

Calculation of the therapeutic activity of radioiodine 131 I for individualized dosimetry in the treatment of Graves’ disease requires an accurate estimate of the thyroid absorbed radiation dose based on a tracer activity administration of 131 I. Common approaches (Marinelli-Quimby formula, MIRD algorithm) use, respectively, the effective half-life of radioiodine in the thyroid and the cumulative activity. Many physicians perform one, two, or at most three tracer dose activity measurements at various times and calculate the required therapeutic activity by ad hoc methods. In this paper, we study the accuracy of estimates of four “target variables”: cumulated activity, effective half-life, maximum activity, and time of maximum activity in the gland. Clinical data from 41 patients who underwent 131 I therapy for Graves’ disease at the University Hospital in Pisa, Italy, are used for analysis. The radioiodine kinetics are described using a nonlinear mixed-effects model that includes a measurement error term, and the distributions of the target variables in the patient population are characterized. Using minimum root mean squared error (RMSE) as the criterion, optimal 1-, 2-, and 3-point sampling schedules are determined for estimation of the target variables, and probabilistic bounds are given for the errors under the optimal designs. An optimization algorithm is developed for computing target variables for arbitrary 1-, 2-, and 3-point activity measurements. Taking into consideration 131 I effective half-life in the thyroid and measurement noise, the optimal 1-point design for cumulated activity is a measurement one week following the tracer dose. Additional measurements give only a slight improvement in accuracy.

Topics: Measurement , Diseases
Commentary by Dr. Valentin Fuster

Bio-Systems and Health Care

2010;():313-320. doi:10.1115/DSCC2010-4061.

In prior work, we have shown that just as in many engineering systems, impedance-like effects appear at the interconnection of biomolecular systems. These effects are called retroactivity, to extend the notion of impedance to biological systems. Signaling components, such as covalent modification cycles, play a central role in the transmission of signals within a cell and from outside the cell. They are typically found in highly interconnected architectures in which a component has several downstream clients. In this paper, we show that retroactivity from downstream targets decreases the sensitivity of response to an input stimulus.

Commentary by Dr. Valentin Fuster
2010;():321-323. doi:10.1115/DSCC2010-4062.

Characterization of multi-variable ankle mechanical impedance is crucial to understanding how the ankle supports lower-extremity function during interaction with the environment. This paper reports quantification of steady-state ankle impedance when muscles were active. Vector field approximation of repetitive measurements of the torque-angle relation in two degrees of freedom (inversion/eversion and dorsiflexion/plantarflexion) enabled assessment of spring-like and non-spring-like components. Experimental results of eight human subjects showed direction-dependent ankle impedance with greater magnitude than when muscles were relaxed. In addition, vector field analysis demonstrated a non-spring-like behavior when muscles were active, although this phenomenon was subtle in the unimpaired young subjects we studied.

Commentary by Dr. Valentin Fuster
2010;():325-332. doi:10.1115/DSCC2010-4066.

This paper describes the design and control of a new monopropellant-powered muscle actuation system for robotic systems, especially the mobile systems inspired by biological principles. Based on the pneumatic artificial muscle, this system features a high power density, as well as characteristics similar to biological muscles. By introducing the monopropellant as the energy storage media, this system utilizes the high energy density of liquid fuel and provides a high-pressure gas supply with a simple structure in a compact form. This addresses the limitations of pneumatic supplies on mobile devices and thus is expected to facilitate the future application of artificial muscles on bio-robotic systems. In this paper, design of the monopropellant-powered muscle actuation system is presented as well as a robust controller design that provides effective control for this highly nonlinear system. To demonstrate the proposed muscle actuation system, an experimental prototype was constructed on which the proposed control algorithm provides good tracking performance.

Topics: Muscle
Commentary by Dr. Valentin Fuster
2010;():333-340. doi:10.1115/DSCC2010-4071.

Chemical distribution is an important factor in many biological systems, driving the phenomenon known as chemotaxis. In order to properly study the effects of various chemical inputs to an in vitro biological assay, it is necessary to have strict control over the spatial distribution of these chemicals. This distribution is typically governed by diffusion, which by nature is a distributed parameter system (DPS), dependent on both space and time. Much study and literature within the controls community has been devoted to DPS, whose dynamics are marked by partial differential equations or delays. They span an infinite-dimensional state-space, and the mathematical complexity associated with this leads to the development of controllers that are often highly abstract in nature. In this paper, we present a method of approximating these systems and expressing them in a manner that makes a DPS amenable to control using a very low order model. In particular, we express the PDE for one-dimensional chemical diffusion as a two-input, two-output state-space system and show that standard controllers can manipulate the outputs of interest, using pole placement and integral control via an augmented state model.

Commentary by Dr. Valentin Fuster
2010;():341-348. doi:10.1115/DSCC2010-4102.

The demand for rehabilitation robots is increasing for the upcoming aging society. Power-assisting devices are considered promising for enhancing the mobility of senior citizen and people with disability. Other potential applications are for muscle rehabilitation and sports training. Various power-assisting devices have been developed for supporting the human joint torque in factory. The main focus of our research is to propose a Pinpointed Muscle Force Control (PMFC) method to control the load of selected muscles by using power-assisting device, thus enabling pinpointed motion support, rehabilitation, and training by explicitly specifying the target muscles. In past research, we have made some achievements. However, using the past control method, all joint torque need to be controlled individually. Limited by the current technology, it is difficult to develop such power-assisting device. In this paper, we developed the muscle force control method by taking into account the control DOF of power-assisting device. Using this method, any existing power-assisting device can be used to realize PMFC, even if this device cannot control all joint torque individually. The validity of this advanced PMFC method and the effects from the control DOF are confirmed in simulation and experiments.

Topics: Force control , Muscle
Commentary by Dr. Valentin Fuster
2010;():349-356. doi:10.1115/DSCC2010-4120.

This paper proposes an estimation method of product usability based on tendon forces. The aim of this study is estimation of product usability using the tendon force during an object manipulation. Proposed method focuses on the forces of the tendons which are connected to the muscles. First, we explain the estimation method of product usability. The product usability is estimated quantitatively from the tendon forces. The tendon skeletal model of the index finger and the thumb is constructed to calculate the tendon forces. The tendon forces are calculated based on grasping information using a tendon skeletal model. Next, the cylinder pinching simulation using the proposed method is shown. The simulation result is compared with the human experimental result to evaluate the effectiveness of the proposed method. The sensory evaluation of the subjective grasp effort was conducted with five subjects. The calculated score of the simulation reflects the questionnaire survey result by the subjects. As an application, we show the evaluation results of the cell-phone button pushing. The calculated score by the simulation is also compared with the human questionnaire score. These results indicate that the proposed method can be used for the quantitative evaluation of the product usability.

Topics: Muscle
Commentary by Dr. Valentin Fuster
2010;():357-364. doi:10.1115/DSCC2010-4139.

This paper presents a method for deriving dynamic equations for Endothelial Cell (EC) motion and estimating parameters based on time lapse imagery of angiogenic sprout development. Angiogenesis is the process whereby a collection of endothelial cells sprout out from an existing blood vessel, degrade the surrounding scaffold and form a new blood vessel. Sprout formation requires that a collection of ECs all work together and coordinate their movements and behaviors. The process is initiated and guided by a collection of external growth factors. In addition, the individual cells communicate and respond to each other’s movements to behave in a coordinated fashion. The mechanics of cell coordination are extremely complex and include both chemical and mechanical communication between cells and between cells and the matrix. Despite the complexity of the physical system, with many variables that cannot be measured in real time, the ECs behave in a predictable manner based on just a few quantities that can be measured in real time. This work presents a methodology for constructing a set of simple stochastic equations for cell motion dependent only on quantities obtained from time lapse data observed from in vitro experiments. Model parameters are identified from time lapse data using a Maximum Likelihood Estimator.

Commentary by Dr. Valentin Fuster
2010;():365-367. doi:10.1115/DSCC2010-4173.

Gait rehabilitation promotes the reduction of gait deficits resulting from neurological pathologies by enhancing activity-dependent plasticity in the central nervous system. To maximize the therapeutic benefit of gait training, the key components appear to be subjects’ active participation and intensity. In this paper we discuss a performance-based training scheme for a novel gait trainer (MIT-Skywalker) that can challenge patients by systematically adjusting the treadmill speed and visual feedback. In our algorithm, the speed is adjusted based on gait performance of step length symmetry and subject’s ability to cope with the treadmill speed. Computer simulations demonstrate that the gait speed controller adapts to changes in walking performance, suggesting a potential scheme for gait therapy.

Commentary by Dr. Valentin Fuster
2010;():369-372. doi:10.1115/DSCC2010-4179.

Bergman’s Minimal Model (MM) captures simply but accurately the homeostasis of glucose and insulin in plasma. The MM has been proposed as an estimator of insulin for Diabetes Mellitus. Along this line of research, the present work takes into account the error between Bergman’s simple compartmental model and the complex physiologic system it depicts. The author employs a Particle Filter (PF) in order to construct the posterior probability density of insulin from data. As a sequential Bayesian estimator, the PF can handle nonlinear state equations, such as the MM, as well as non-Gaussian modeling error. These advantages of the PF over the Kalman Filter warrant further consideration for insulin estimation and, in turn, avoidance of hyperinsulinemia.

Commentary by Dr. Valentin Fuster
2010;():373-380. doi:10.1115/DSCC2010-4183.

Current commercially available motorized replacement limbs rely on the activation of remaining muscle tissue or a different portion of the body to operate joints in the prosthetic, which requires training to use and may never feel natural. Research to improve artificial limb technology is focused on using implants to monitor electrical activity in the nervous system or rerouting nerve endings to healthy muscle tissue, both of which require a medical procedure to be performed. This paper presents results of research which has been focused on the feasibility of using a non-invasive prosthetic control system that utilizes a hybrid of feedforward and feedback sensors. This research examines the correlation between brain activity across the primary motor cortex and muscle activity during upper body limb movement. The hybrid sensory system is composed of an optical imager for the detection of localized brain activities, electroencephalography (EEG) and electromyography (EMG) sensors. This paper will present design of the sensory system, the proposed control architecture, and human subject results. The improved accuracy of the brain intention determination algorithm as well as integration with a learning control loop will be presented and discussed.

Commentary by Dr. Valentin Fuster
2010;():381-388. doi:10.1115/DSCC2010-4185.

Surface Electromyographic (sEMG) signals have been exploited for almost a century, for various clinical and engineering applications. One of the most compelling and altruistic applications being, control of prosthetic devices. The study conducted here looks at the modeling of the force and sEMG signals, using nonlinear Hammerstein-Weiner System Identification techniques. This study involved modeling of sEMG and corresponding force data to establish a relation which can mimic the actual force characteristics for a few particular hand motions. Analysis of the sEMG signals, obtained from specific Motor Unit locations corresponding to the index, middle and ring finger, and the force data led to the following deductions; a) Each motor unit location has to be treated as a separate system, (i.e. extrapolation of models for different fingers cannot be done) b) Fatigue influences the Hammerstein-Wiener model parameters and any control algorithm for implementing the force regimen will have to be adaptive in nature to compensate for the changes in the sEMG signal and c) The results also manifest the importance of the design of the experiments that need to be adopted to comprehensively model sEMG and force.

Commentary by Dr. Valentin Fuster
2010;():389-396. doi:10.1115/DSCC2010-4186.

Walking impairments are a common sequela of neurological injury, severely affecting the quality of life of both adults and children. Gait therapy is the traditional approach to ameliorate the problem by re-training the nervous system and there have been some attempts to mechanize such approach. In this paper, we present a novel impedance controller for the MIT-Skywalker. In contrast to previous approaches in mechanized gait therapy, the MIT-Skywalker does not impose a rigid kinematics pattern of normal gait on impaired walkers. Instead, it takes advantage of the concept of passive walkers and the natural dynamics of the lower extremity in order to deliver more “ecological” therapy. The proposed closed-loop control scheme can regulate the interaction between the walker and the treadmill and can provide the appropriate feedback to the walker during stance phase as well as at heel-strike and toe-off. Simulation results prove the feasibility of the impedance-based control scheme.

Commentary by Dr. Valentin Fuster
2010;():397-404. doi:10.1115/DSCC2010-4190.

Cell migration is fundamental to a wide range of biological and physiological functions including: wound healing, immune defense, cancer metastasis, as well as the formation and development of biological structures such as vascular and neural networks. In these diverse processes, cell migration is influenced by a broad set of external mechanical and biochemical cues, particularly the presence of (time dependent) spatial gradients of soluble chemoattractants in the extracellular domain. Many biological models have been proposed to explain the mechanisms leading to the migratory response of cells as a function of these external cues. Based on such models, here we propose approaches to controlling the chemotactic response of eukaryotic cells by modulating their micro-environments in vitro (for example, using a microfluidic chemotaxis chamber). By explicitly modeling i) chemoattractant-receptor binding kinetics, ii) diffusion dynamics in the extracellular domain, and iii) the chemotactic response of cells, models for the migration processes arise. Based on those models, optimal control formulations are derived. We present simulation results, and suggest experimental approaches to controlling cellular motility in vitro, which can be used as a basis for cellular manipulation and control.

Commentary by Dr. Valentin Fuster
2010;():405-411. doi:10.1115/DSCC2010-4204.

Repetitive task-oriented exercises are accepted in traditional gait rehabilitation and have given rise to driven gait orthoses, but both methods suffer from limited rehabilitation time for the patient. The presented device proposes a control strategy and implementation unique for a mobile rehabilitation exoskeleton as well as results from initial subject testing. This anthropomorphically designed device has knee and hip joints that are actuated in the sagittal plane using hydraulic actuators. The presented control strategy allows the user or therapist to directly specify the level of rehabilitation assistance desired between complete machine control and a zero impedance joint. The device was experimentally tested on three chronic stroke patients with noticeable gait improvements based on the metric of joint flexion. Other results of step time and step length are presented that do not demonstrate as clear improvements but these are believed to be a function of the limited patient testing time.

Commentary by Dr. Valentin Fuster
2010;():413-420. doi:10.1115/DSCC2010-4218.

The lateral nucleus of amygdala (LA) is known to be a critical storage site for conditioned fear memory. Synaptic plasticity at auditory inputs to the dorsal LA (LAd) is critical for the formation and storage of auditory fear memories. Recent evidence suggests that two different cell populations (transient- and long-term plastic cells) are present in LAd and are responsible for fear learning. However, the mechanisms involved in the formation and storage of fear are not well understood. As an extension of previous work, a biologically realistic computational model of the LAd circuitry is developed to investigate these mechanisms. The network model consists of 52 LA pyramidal neurons and 13 interneurons. Auditory and somatosensory information reaches LA from both thalamic and cortical inputs. The model replicated the tone responses observed in the two LAd cell populations during conditioning and extinction. The model provides insights into the role of thalamic and cortical inputs in fear memory formation and storage.

Commentary by Dr. Valentin Fuster
2010;():421-428. doi:10.1115/DSCC2010-4222.

Piezoelectrically driven cellular actuators are a technology inspired by biological muscles. Like muscle tissue, several serial and parallel combinations act in concert to achieve the desired motion. In order to simplify the drive electronics and mitigate the effect of hysteresis in piezoelectric materials, it is desired to restrict each input to simple on-off commands. This quantizes the actuation greatly. The cellular actuators also have a number of lightly damped flexible modes, which may be higher than the Nyquist frequency of the discrete–time controller. These may still cause long settling times. We propose a method to convert a continuously variable control input from a controller whose design does not consider quantization and flexible effects to a quantized signal that can be implemented by the actuator which also reduces oscillation in known lightly damped modes.

Commentary by Dr. Valentin Fuster
2010;():429-431. doi:10.1115/DSCC2010-4224.

This article compares stochastic estimates of multi-variable human ankle mechanical impedance when ankle muscles were fully relaxed, actively generating ankle torque or co-contracting antagonistically. We employed Anklebot, a rehabilitation robot for the ankle, to provide torque perturbations. Muscle activation levels were monitored electromyographically and these EMG signals were displayed to subjects who attempted to maintain them constant. Time histories of ankle torques and angles in the Dorsi-Plantar flexion (DP) and Inversion-Eversion (IE) directions were recorded. Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot alone and when it was worn by a human subject, the difference between these functions providing an estimate of ankle mechanical impedance. High coherence was observed over a frequency range up to 30 Hz. The main effect of muscle activation was to increase the magnitude of ankle mechanical impedance in both DP and IE directions.

Commentary by Dr. Valentin Fuster
2010;():433-435. doi:10.1115/DSCC2010-4242.

Cardiac alternans is a marker of sudden cardiac arrest, the leading cause of death in the United States that kills hundreds of thousands of Americans each year. In the language of nonlinear dynamics, the onset of cardiac alternans is induced by a period-doubling bifurcation. In this work, we explore the bifurcation and control of cardiac alternans in a fiber based on numerical analyses of the seminal amplitude equation derived by Echebarria and Karma. First, we seek the solution of the amplitude equation using a series expansion. Then, detailed numerical bifurcation analyses are carried out to illustrate the spatiotemporal patterns of cardiac alternans. We demonstrate that secondary bifurcations lead to multiple unstable patterns, which impose difficulties in feedback control of alternans. Effects and limitations of feedback control algorithms are explored. The theoretical analyses here help to improve the understanding of the mechanisms of alternans in cardiac tissue.

Topics: Bifurcation
Commentary by Dr. Valentin Fuster
2010;():437-443. doi:10.1115/DSCC2010-4243.

Electroporation is an elegant means to deliver molecules into the cellular cytoplasm, while simultaneously maintaining cell viability and functionality. Despite extensive research, however, electroporation methods still fall short of the desired efficiency and reliability. We present a model predictive control (MPC) design for enabling highly efficient and reliable electroporation processes. Instead of using one single electrical pulse in current practice, we consider a controlled multi-pulse electroporation based on an MPC framework. The most attractive properties of using MPC design of multi-pulse electroporation are the fast computation of optimal control solutions and the real-time tunability of the electrical field density during the process. We demonstrate the controlled electroporation process through simulation examples.

Commentary by Dr. Valentin Fuster
2010;():445-451. doi:10.1115/DSCC2010-4246.

A cell’s behavior in response to stimuli is governed by a signaling network, called cue-signal-response. Endothelial Cells (ECs), for example, migrate towards the source of chemo-attractants by detecting cues (chemo-attractants and their concentration gradient), feeding them into an intra-cellular signaling network (coded internal state), and producing a response (migration). It is known that the cue-signal-response process is a nonlinear, dynamical system with high dimensionality and stochasticity. This paper presents a system dynamics approach to modeling the cue-signal-response process for the purpose of manipulating and guiding the cell behavior through feedback control. A Hammerstein type model is constructed by representing the entire process in two stages. One is the cue-to-signal process represented as a nonlinear feedforward map, and the other is the signal-to-response process as a stochastic linear dynamical system, which contains feedback loops and auto-regressive dynamics. Analysis of the signaling space based on Singular-Value Decomposition yields a set of reduced order synthetic signals, which are used as inputs to the dynamical system. A prediction-error method is used for identifying the model from experimental data, and an optimal system order is determined based on Akaike’s Information Criterion. The resultant low order model is capable of predicting the expected response to cues, and is directly usable for feedback control. The method is applied to an in vitro angiogenic process using microfluidic devices.

Topics: Modeling , Signals
Commentary by Dr. Valentin Fuster
2010;():453-458. doi:10.1115/DSCC2010-4261.

Spinal cord injuries leave thousands of patients confined to wheelchairs, resulting in a life of severely limited mobility. This condition also subjects them to the risk of secondary injuries. Because exoskeletons are externally driven machines in which the actuation is coupled to the person’s joints, they offer an ideal method to help paraplegics walk. The exoskeleton presented here is a mobile, battery powered device that uses hydraulically actuated hip and knee joints in the sagittal plane to move a patient’s joints. The control strategy mimics standard human walking using foot sensors to determine the walking state. This activates position control of the joints to follow standard walking trajectories based on clinical gait analysis data. Initial patient testing of the device showed that the exoskeleton enabled one incomplete paraplegic to significantly improve his gait function and three complete paraplegic patients to walk.

Commentary by Dr. Valentin Fuster
2010;():459-465. doi:10.1115/DSCC2010-4272.

The preparation of specimens for cryo-electron microscopy is currently a labor and time intensive process, and the quality of resulting samples is highly dependent on both environmental and procedural factors. Specimens must be applied to sample grids in a high-humidity environment, frozen in liquid ethane, and stored in liquid nitrogen. The combination of cryogenic temperatures and humidity-control mandates the segregation of the humidity-controlled environment from the cryogenic environment. Several devices which automate portions of the specimen preparation process are currently in use; however, these systems still require significant human interaction in order to create viable samples. This paper describes a fully automated system for specimen preparation. The resulting system removes the need for human input during specimen preparation, improves process control, and provides similar levels of environmental control. Early testing shows that the resulting system is capable of manipulating samples in an autonomous manner while providing performance similar to existing systems.

Topics: Electrons , Microscopy
Commentary by Dr. Valentin Fuster
2010;():467-472. doi:10.1115/DSCC2010-4274.

This article presents the results of two in-vivo studies providing measurements of human static ankle mechanical impedance. Accurate measurements of ankle impedance when muscles were voluntarily activated were obtained using a therapeutic robot, Anklebot, and an electromyographic recording system. Important features of ankle impedance, and their variation with muscle activity, are discussed, including magnitude, symmetry and directions of minimum and maximum impedance. Voluntary muscle activation has a significant impact on ankle impedance, increasing it by up to a factor of three in our experiments. Furthermore, significant asymmetries and deviations from a linear two-spring model are present in many subjects, indicating that ankle impedance has a complex and individually idiosyncratic structure. We propose the use of Fourier series as a general representation, providing both insight and a precise quantitative characterization of human static ankle impedance.

Commentary by Dr. Valentin Fuster
2010;():473-480. doi:10.1115/DSCC2010-4287.

The thyroid, the largest gland in the endocrine system, secretes hormones that regulate homeostatic functions within the body and promote normal growth and development. Recently, a detailed computational model of the thyroid gland has been derived and used to explain clinical observations regarding the thyroid gland’s ability to maintain its hormonal secretion target in the face of uncertain dietary iodine intake levels. In this paper we probe deeper into the thyroid’s nonlinear dynamics. We first reduce the original model to an eight-order dynamical system, analytically determine that a Hopf mechanism governs the loss of stability of thyroid equilibrium, culminating with numerically obtained periodic limit-cycle behavior beyond the critical threshold. We numerically investigate the orbital stability of periodic thyroid dynamics via its harmonic perturbation and construct a bifurcation structure that includes both periodic and subharmonic mode-locked solutions embedded within a set of quasiperiodic tori. An increase of the perturbation parameter reveals a similar and structurally stable bifurcation structure. Thus, the analysis of our nonlinear thyroid model shows that the gland can exhibit both a stable equilibrium and periodic limit-cycle behavior which can lose its orbital stability due to small harmonic perturbations.

Commentary by Dr. Valentin Fuster

Control of Electric Vehicles

2010;():481-488. doi:10.1115/DSCC2010-4136.

EPACs (Electric Pedal Assisted Cycles) represent a very efficient and fashionable mean of non-polluting transport. They are useful for bringing education, for health service and they guarantee the lowest energy cost per distance traveled. In this paper, a power kit has been designed and implemented on a real electric bicycle. In particular, hardware architectures and control algorithms are developed together, taking in account shared needs. An optimal choice of the components and an innovative overboost strategy characterize the provided system. Experimental results and comparison with a benchmark product available in the market demonstrate the efficiency of the whole system.

Commentary by Dr. Valentin Fuster
2010;():489-497. doi:10.1115/DSCC2010-4197.

This paper examines the problem of predicting the aggregate grid load imposed by battery health-conscious plug-in hybrid electric vehicle (PHEV) charging. The paper begins by generating a set of representative daily PHEV trips using the National Household Travel Survey (NHTS) and a set of federal and real-world drive cycles. Each trip is then used in a multiobjective genetic optimizer, along with a PHEV model and a battery degradation model, to simultaneously minimize PHEV energy cost and battery degradation. The optimization variables include the parameters of the PHEV charge pattern, defined as the timing and rate with which the PHEV receives electricity from the grid. For several weightings of the optimization objectives, total PHEV power demand is predicted by accumulating the charge patterns for individual PHEVs. Two charging scenarios, i.e., charging at home only versus charging at home and work, are examined. Results indicate that the main PHEV peak load occurs early in the morning (between 5.00–6.00a.m.), with approximately 45%–60% of vehicles simultaneously charging from the grid. Moreover, charging at work creates additional peaks in this load pattern.

Commentary by Dr. Valentin Fuster
2010;():499-505. doi:10.1115/DSCC2010-4211.

This paper proposes a new method for solving the energy management problem for hybrid electric vehicles (HEVs) based on the equivalent consumption minimization strategy (ECMS). After discussing the main features of ECMS, an adaptation law of the equivalence factor used by ECMS is presented, which, using feedback of state of charge, ensures optimality of the strategy proposed. The performance of the A-ECMS is shown in simulation and compared to the optimal solution obtained with dynamic programming.

Commentary by Dr. Valentin Fuster
2010;():507-514. doi:10.1115/DSCC2010-4233.

Dynamic programming (DP) provides the optimal global solution to the energy management problem for hybrid electric vehicles (HEVs), but needs complete a-priori knowledge of the driving cycle and has high computational requirements. This article presents a possible methodology to extract rules from the dynamic programming solution to design an implementable rule-based strategy. The case study considered is a series/parallel HEV, in which a clutch allows to switch from one configuration to another. The strategy works according to a two layer policy: the supervisory controller, which decides the powertrain configuration (either series or parallel), and the energy management, which decides the power split. The process of deriving the rules from the optimal solution is described. Then, the performance of the resulting rule-based strategy is studied and compared with the solution given by the dynamic programming, which functions as a benchmark.

Commentary by Dr. Valentin Fuster
2010;():515-522. doi:10.1115/DSCC2010-4255.

This paper presents a fault-tolerant control method for four-wheel independently driven (4WID) electric vehicles. 4WID electric vehicle is one of the promising architectures for electric vehicles in the future. While such a vehicle architecture greatly increases the flexibility for vehicle control, it also demands more on system reliability, safety, and fault tolerance due to the increased number of actuators and subsystems. An active fault tolerant control approach for 4WID electric vehicle is developed to accommodate the fault of in-wheel motor and motor driver pairs. Based on an in-wheel motor/motor driver fault detection mechanism, a control-allocation based vehicle control system is designed to accommodate the in-wheel motor/motor driver fault by automatically allocating the control effort among other healthy wheels. Simulations using a high-fidelity CarSim® full-vehicle model show the effectiveness of the proposed fault-tolerant control approach.

Topics: Vehicles , Wheels
Commentary by Dr. Valentin Fuster

Control of Linear Systems

2010;():523-530. doi:10.1115/DSCC2010-4040.

The problem of compensation of infinite-dimensional actuator or sensor dynamics of more complex type than pure delay was solved recently using the backstepping method for PDEs. In this paper we construct an explicit feedback law for a multi-input LTI system which compensates the wave PDE dynamics and stabilizes the overall system. Our design is based on a novel infinite-dimensional backstepping-forwarding transformation. We illustrate the effectiveness of our design with a simulation example of a single-input second order system, in which the wave input enters the system through two different channels, each one located at a different point in the domain of the wave PDE. Finally, we consider a dual problem where we design an exponentially convergent observer that compensates the distributed effect of the wave sensor dynamics.

Topics: Waves
Commentary by Dr. Valentin Fuster
2010;():531-537. doi:10.1115/DSCC2010-4082.

A class of linear time-invariant (LTI) consensus system with multiple agents and communication delays among the agents is studied. The delay margin of this MIMO system, that is, the largest amount of the delay that the system can withstand without loosing stability, can be studied by the authors’ Responsible Eigenvalue (RE) concept. RE is able to compress the considered stability problem into the stability problem of a single agent system, from which RE captures the delay margin of the entire MIMO system. RE is used here to design controllers for the MIMO system for the objective of increasing the delay margin. Case studies demonstrate connections between coupling strengths, graph Laplacian, the delay margin of a large-scale consensus system, and control synthesis.

Commentary by Dr. Valentin Fuster
2010;():539-546. doi:10.1115/DSCC2010-4191.

In this work we consider the problem of parametrizing the set of all stabilizing Linear Time-Invariant (LTI) controllers for multirate systems such that model matching is achieved with a desired transfer function. We consider those systems where the plant output can be measured at a rate (measurement update rate) slower than the control signal updates rate. The solution to the parametrization problem is provided for the two cases: (1) model matching at the control update rate, (2) model matching at the measurement update rate. Unlike model matching at the measurement update rate, model matching at the control update rate allows us to directly improve and characterize the transient response of the continuous-time system. Tools such as up-sampling and down-sampling operators, and modified Z-transforms are utilized to model the closed-loop multirate system and to parametrize the sets of LTI controllers.

Commentary by Dr. Valentin Fuster
2010;():547-553. doi:10.1115/DSCC2010-4195.

In this paper, a new methodology for robust control design of linear systems with time varying real parameter uncertainty is presented. The distinctive feature of this method is that it specifically offers robustness guarantees to real parameter uncertainty thereby providing a much needed alternative design method compared to existing design methods such as H∞ and μ-synthesis methods which tend to be conservative when specialized to real parameter uncertainty. The proposed robust control design method is inspired by sign (qualitative) stability idea from ecology, leading to a specific structure in the desired closed loop system matrix involving pseudosymmetry. The design procedure is simple and straightforward without requiring intensive computation. The proposed design algorithm is illustrated with aerospace applications. This algorithm is quite promising with considerable scope for extensions and improvements, finally adding to the bank of available control design methods for linear state space systems.

Commentary by Dr. Valentin Fuster
2010;():555-562. doi:10.1115/DSCC2010-4210.

This paper presents results that can be used to validate input-output transient performance for modular control systems. If bounds in the time-domain are specified for inputs of an LTI SISO system, the techniques in this paper can determine the minimum set containing all possible outputs. If both input and output bounds are given, they can determine whether these specifications are met. Network delay affecting the input of the system is also considered. Finally, this paper extends the techniques for MIMO systems. The results are derived using the theory of convex sets. Several examples are presented to illustrate the results and demonstrate their application.

Topics: Control systems
Commentary by Dr. Valentin Fuster
2010;():563-569. doi:10.1115/DSCC2010-4271.

In this paper, we extend previous results for a novel internal model-based tracking control with a class of known LTV plant models driven by LTI exosystems to uncertain LTI plant models driven by LTV exosystems. The augmented time-varying system to be stabilized becomes uncertain. Moreover, the time-varying fashion under consideration renders the augmented uncertain system linear parameter-varying (LPV). By means of an output-feedback gain-scheduling design, the augmented uncertain LTV system is stabilized. Simulation results illustrate the proposed design method.

Commentary by Dr. Valentin Fuster

Control Theory

2010;():571-578. doi:10.1115/DSCC2010-4033.

Many industrial processes employ radiation-based actuators with two or more manipulated variables. Moving radiant actuators, in particular, act on a distributed parameter process where the velocity of the actuator is an additional manipulated variable with its own constraints. In this paper, a model predictive control (MPC) scheme is developed for a distributed-parameter process employing such a moving radiant actuator. The designed MPC controller uses an online optimization approach to determine both the radiant intensity and velocity of the moving actuator based on a linearized process model and a distributed state/parameter estimator. A particular source-model reduction that enables the approach is outlined. The proposed strategy is then demonstrated for a radiative curing process considering different control scenarios with the objective of achieving desired cure level uniformity and minimizing process energy use.

Commentary by Dr. Valentin Fuster
2010;():579-581. doi:10.1115/DSCC2010-4063.

This article introduces a general formulation of model based iterative learning control (ILC). The formulation is valid for both linear and nonlinear systems. It is a two step approach, such that after each repetition of the task two (non)linear least squares problems have to be solved. In the first step an optimal model correction is calculated. This is a nonparametric correction to the model in order to describe the measured output signal more accurately. This model correction is used in the second step, which is a model inversion problem. Conventional linear ILC is shown to be a particular case of this general formulation.

Commentary by Dr. Valentin Fuster
2010;():583-590. doi:10.1115/DSCC2010-4108.

This paper considers an output regulation problem for a class of discrete-time switched bimodal linear systems against known deterministic exogenous signals in the presence of unknown random disturbances, which is motivated by the flying height regulation problem in hard disk drives. The regulation problem for the switched system against the known deterministic exogenous signals is approached by constructing a set of observer-based parameterized stabilizing controllers that satisfy a sufficient regulation condition for the switched system. An H2 performance constraint is then added to identify, from among the already constructed regulators, those that provide the best H2 performance against the unknown random disturbances. The proposed regulator is successfully evaluated on a bimodal switched mechanical system experimental setup to demonstrate the effectiveness of the proposed regulation approach.

Commentary by Dr. Valentin Fuster
2010;():591-598. doi:10.1115/DSCC2010-4282.

Iterative learning control (ILC) is a feedforward control strategy used to improve the performance of a system that executes the same task repeatedly, but is incapable of compensating for non-repetitive disturbances. Thus a well-designed feedback controller needs to be used in combination with ILC. A robustness filter called the Q-filter is essential for the ILC system stability. The price to pay, however, is that the Q-filter makes it impossible for ILC to achieve perfect tracking of the repetitive reference or perfect cancellation of repetitive disturbances. To reduce error, it is effective to apply a pre-design feedforward control input in addition to ILC. In this paper, a simple P-type ILC is combined with an optimal feedback-feedforward control inspired by classic predictive control, so as to take advantages of each control strategy. It will be shown that the choice of the injection point of the learned ILC effort is crucial for a tradeoff between stability and performance. Therefore, the stability and performance analysis based on different injection points is studied. A systematic approach to the combined control scheme is also proposed. The combined control scheme is attractive due to its simplicity and promising performance. The effectiveness of the combined control scheme is verified by simulation results with a wafer scanner system.

Commentary by Dr. Valentin Fuster
2010;():599-605. doi:10.1115/DSCC2010-4297.

The major benefit of the kinematic Kalman filter (KKF), i.e., the state estimation based on kinematic model is that it is immune to parameter variations and unknown disturbances regardless of the operating conditions. In carrying out complex motion tasks such as the coordinated manipulation among multiple machines, some of the motion variables measured by sensors may only be available through the communication layer, which requires to formulate the optimal state estimator subject to lossy network. In contrast to standard dynamic systems, the kinematic model used in the KKF relies on sensory data not only for the output but also for the process input. This paper studies how the packet dropout occurring from the input sensor as well as the output sensor affects the performance of the KKF. When the output sensory data are delivered through the lossy network, it has been shown that the mean error covariance of the KKF is bounded for any non-zero packet arrival rate. On the other hand, if the input sensory data are subject to lossy network, the Bernoulli dropout model results in an unbounded mean error covariance. More practical strategy is to adopt the previous input estimate in case the current packet is dropped. For each case of packet dropout models, the stochastic characteristics of the mean error covariance are analyzed and compared. Simulation results are presented to illustrate the analytical results and to compare the performance of the time varying (optimal) filter gain with that of the static (sub-optimal) filter gain.

Commentary by Dr. Valentin Fuster

Electric Battery Modeling and Control

2010;():607-614. doi:10.1115/DSCC2010-4085.

Lithium-ion batteries are a growing source for electric power, but must be maintained within acceptable operating conditions to ensure efficiency and reliability. Therefore, a robust fault detection and isolation scheme is required that is sensitive enough to determine when sensor or actuator faults present a threat to the health of the battery. A scheme suitable for a hybrid electric vehicle battery application is presented in this work. The diagnostic problem is formulated as a nonlinear parity equation approach, but is modified for the considered application. Sliding mode observers are designed for input estimation, while the output voltage estimation is performed using an open loop model. The selection of optimal thresholds given a maximum allowable probability of error is also considered. An assessment of the design using real-world driving-cycle data leads to the conclusion that the estimation error of the observers determines a lower bound on the minimum detectable fault magnitude.

Commentary by Dr. Valentin Fuster
2010;():615-624. doi:10.1115/DSCC2010-4089.

This paper investigates power management algorithms that optimally manage lithium-ion battery pack health, in terms of anode-side film growth, for plug-in hybrid electric vehicles (PHEVs). Specifically, we integrate a reduced electrochemical model of solid electrolyte interface (SEI) film formation into a stochastic dynamic programming formulation of the PHEV power management problem. This makes it possible to optimally trade off energy consumption cost versus battery health. A careful analysis of the resulting Pareto-optimal set of power management solutions provides two important insights into the tradeoffs between battery health and energy consumption cost in PHEVs. First, optimal power management solutions that minimize energy consumption cost tend to ration battery charge, while the solutions that minimize battery health degradation tend to deplete charge aggressively. Second, solutions that balance the needs for minimum energy cost and maximum battery health tend to aggressively deplete battery charge at high states of charge (SOCs), then blend engine and battery power at lower SOCs. These results provide insight into the fundamental tradeoffs between battery health and energy cost in PHEV power management.

Commentary by Dr. Valentin Fuster
2010;():625-631. doi:10.1115/DSCC2010-4199.

Li-ion batteries are today considered the prime solution as energy storage system for EV/PHEV/HEV, due to their high specific energy and power. Since their performance, life and reliability are influenced by the operating temperature, great interest has been devoted to study different cooling solutions and control algorithms for thermal management. In this context, this paper presents a computationally efficient modeling approach to characterize the internal temperature distribution of a Li-ion battery cell, conceived to serve as a tool to aid the design of cooling systems and the development of thermal management systems for automotive battery packs. The model is developed starting from the unsteady heat diffusion equation, for which an analytical solution is obtained through the integral transform method. First, a general one-dimensional thermal model is developed to predict the temperature distribution inside a prismatic Li-ion battery cell under different boundary conditions. Then, a specific case with convective boundary conditions is studied with the objective of characterizing a cell cooled by a forced air flow. To characterize the effects of the cooling system on the temperature distribution within the cell, the one-dimensional solution is then extended to a 1+1D model that accounts for the variability of the boundary conditions in the flow direction. The calibration and validation of the specific model presented will be presented, adopting a detailed 2D FEM simulator as a benchmark.

Commentary by Dr. Valentin Fuster
2010;():633-640. doi:10.1115/DSCC2010-4200.

The thermal characterization of Li-ion batteries for EVs, HEVs and PHEVs is a topic of great relevance, especially for the evaluation of the battery pack state of health (SoH) during vehicle operations and for battery life estimation. This work proposes a reduced-order model that estimates the thermal dynamics of a cylindrical Li-ion battery cell, with respect to time-varying current demands. Unlike most “black-box” dynamic models, based on system identification techniques, the proposed approach relies on the definition of a boundary-value problem for heat conduction, in the form of a linear partial differential equation. The problem is then converted into a low-order linear model by applying model-order reduction method in the frequency domain. The resulting model predicts the temperature dynamics at the center and at the external surface in relation with the rate of heat generation and the coolant temperature. In this paper, the model is applied to estimate the internal temperature of a cylindrical cell during a discharging transient. The model uses electrical data acquired from experimental tests and is validated by comparison with experimental data and 3D FEM thermal simulation.

Commentary by Dr. Valentin Fuster

Engine Control

2010;():641-648. doi:10.1115/DSCC2010-4024.

Control oriented model (COM) using crank-angle resolved flame propagation simulation and nonlinear model predictive control (NMPC) methodology for the purpose of transient control of HDOF engines are proposed in this paper. The nonlinear nature of the combustion process has been a challenge in building a reliable COM and engine simulation. Artificial neural networks (ANNs) are subsequently trained on the data generated with a quasi-D combustion model to create fast surrogate combustion models. System dynamics are augmented by manifold and actuator dynamics models. Then, NMPC for an internal combustion (IC) engine with a dual-independent variable valve timing (VVT) system is designed to achieve fast torque responses, to eliminate exhaust emissions penalty, and to track the optimal actuator response closely. The NMPC significantly improves engine dynamics and minimizes excursions of in-cylinder variables under highly transient operation. Dead-beat like control is achieved with selected prediction horizon and control horizon in the NMPC.

Commentary by Dr. Valentin Fuster
2010;():649-656. doi:10.1115/DSCC2010-4038.

This paper applies integrated system modeling and control design process to a continuously variable valve timing (VVT) actuator system that has different control input and cam position feedback sample rates. Due to high cam shaft torque disturbance and high actuator open-loop gain, it is fairly difficult to maintain the cam phase at the desired constant level with an open-loop controller. As a result, multirate closed-loop system identification is a necessity. For this study, multirate closed-loop system identification, PRBS q-Markov Cover, was used for obtaining linearized system models at different engine operational conditions; and the output covariance constraint (OCC) controller, an H2 controller, was designed based upon the identified model and evaluated on the VVT test bench. Performances of the designed OCC controller was compared with those of the baseline PI controller on the test bench. Results show that the OCC controller uses less control effort and has less overshoot than those of PI ones.

Commentary by Dr. Valentin Fuster
2010;():657-664. doi:10.1115/DSCC2010-4042.

The combustion mode transition between SI (spark ignited) and HCCI (Homogeneously Charged Compression Ignition) of an IC (Internal Combustion) engine is challenge due to the thermo inertia of residue gas; and model-based control becomes a necessity. This paper presents a control oriented two-zone model to describe the hybrid combustion that starts with SI combustion and ends with HCCI combustion. The gas respiration dynamics were modeled using mean-value approach and the combustion process was modeled using crank resolved method. The developed model was validated in an HIL (Hardware-In-the-Loop) simulation environment for both steady-state and transient operations in SI, HCCI, and SI-HCCI hybrid combustion modes through the exhaust valve timing control (recompression). Furthermore, cooled external EGR (exhaust gas re-circulation) was used to suppress engine knock and enhance the fuel efficiency. The simulation results also illustrates that the transient control parameters of hybrid combustion is quite different from these in steady state operation, indicating the need of a control oriented SI-HCCI hybrid combustion model for transient combustion control.

Commentary by Dr. Valentin Fuster
2010;():665-672. doi:10.1115/DSCC2010-4087.

The three way catalytic converter (TWC) is a critical component for the mitigation of tailpipe emissions of modern internal combustion (IC) engines. Because the TWC operates effectively only when the air-fuel ratio is very close to stoichiometric, accurate control of the air-fuel ratio is required. The dynamics of the IC engine can be modeled as a first order plus dead time for controller design purposes and vary with both engine speed and air flow. Traditional control schemes using time-invariant controllers have been successful in guaranteeing stability over the operating range of the engine but have introduced a degree of conservatism. To reduce the conservatism, a gain scheduling controller taking both engine speed and air flow as scheduling parameters is proposed. A linear parameter varying model of the plant is constructed and the controller design method is formulated in terms of linear matrix inequalities yielding a convex optimization problem. The resulting closed-loop system has guaranteed stability and performance over the designed operating range of the engine. Simulations are performed to validate and compare the controller with a time-invariant controller as well as a gain scheduling controller that takes only engine speed as a scheduling parameter.

Commentary by Dr. Valentin Fuster
2010;():673-678. doi:10.1115/DSCC2010-4177.

This article shows a new excitation method for the identification of combustion engines. The method is based on the combination of statistical stationary engine measurement (Design of Experiments - DoE) and dynamic identification techniques for nonlinear multi-input systems. The dynamics are excited by special amplitude-modulated pseudo-random-multilevel-signals (APRMS), which act on the engine simultaneously, in order to allow a short measurement time period. Because the used dynamic excitation signals are orthogonal, they allow a better separation of the input signals for system identification.

Topics: Combustion , Engines , Signals
Commentary by Dr. Valentin Fuster
2010;():679-686. doi:10.1115/DSCC2010-4266.

An inverse dynamics scheme, based on a detailed differential-algebraic model of the crank-slider mechanism of a single cylinder internal combustion (IC) engine, is developed for the computation of the instantaneous frictional losses of engine components. The proposed approach requires accurate measurements of the independent and superfluous coordinates of the crank-slider mechanism as well as their time derivatives. This was achieved by implementing a sliding mode observer, previously developed by the authors, to provide the required estimates of the state variables. The aforementioned observer is suitable for use with differential-algebraic nonlinear equations of motion and was shown to be robust to both modeling imprecision and external disturbances. The digital simulation results show the capability of the combined inverse dynamics scheme with the observer in producing good estimates of the instantaneous frictional losses of the various engine components.

Commentary by Dr. Valentin Fuster

Engine/Emission Controls

2010;():687-694. doi:10.1115/DSCC2010-4010.

NO and NO2 are generally considered together as NOx in engine emissions. Since NO2 /NOx ratio is small in diesel engine exhaust gas, very often, existence of NO2 is ignored in studies/applications. However, current diesel aftertreatment systems generally include diesel oxidation catalysts (DOCs) at upstream of other catalysts such as diesel particulate filter (DPF) and selective catalytic reduction (SCR). DOC can significantly increase the NO2 fraction in the exhaust NOx . Because NO2 and NO have completely different reaction characters within catalysts, e.g. NO2 can assist DPF regeneration while NO cannot, and SCR De-NOx rate can be increased with higher NO2 /NOx ratio (no more than 0.5), considerations of NO2 in aftertreatment systems are becoming necessary. Nevertheless, current onboard NOx sensors cannot differentiate NO and NO2 from NOx . This induces an interest in the method of estimating the concentrations of NO and NO2 in the exhaust gas by available measurements. In this paper, a physically-based, DOC control-oriented model which considers the NO and NO2 related dynamics and an engine exhaust NO/NO2 prediction method were proposed for the purposes of NO/NO2 ratio estimation in diesel engine aftertreatment systems, and the developed model was validated with experimental data.

Commentary by Dr. Valentin Fuster
2010;():695-702. doi:10.1115/DSCC2010-4011.

This paper presents a physically-based, control-oriented Diesel particulate filter (DPF) model for the purposes of NO and NO2 concentration estimations in Diesel engine aftertreatment systems. The presence of NO2 in exhaust gas plays an important role in selective catalytic reduction (SCR) NOx reduction efficiency. However, current NOx cannot differentiate NO and NO2 from the total NOx concentration. A model which can be used to estimate NO and NO2 concentrations in exhaust gas flowing into the SCR catalyst is thus necessary. Current aftertreatment systems for light-, medium-, and heavy-duty Diesel engines generally include Diesel oxidation catalyst (DOC), DPF, and SCR. The DPF related NO/NO2 dynamics was investigated in this study, and a control-oriented model was developed and validated with experimental data.

Commentary by Dr. Valentin Fuster
2010;():703-710. doi:10.1115/DSCC2010-4075.

In this paper, an event-based sampled discrete-time linear system representing a port-fuel-injection process based on wall-wetting dynamics is obtained and formulated as a linear parameter varying (LPV) system. The system parameters used in the engine fuel system model are engine speed, temperature, and load. These system parameters can be measured in real-time through physical or virtual sensors. A gain-scheduling controller for the obtained LPV system is then designed based on the numerically efficient convex optimization or linear matrix inequality (LMI) technique. To demonstrate the feasibility of implementing the gain-scheduling controller, a hardware-in-the-loop (HIL) simulation is performed using a mixed mean-value and crank-based engine model. The HIL results show the effectiveness and implementability of the proposed scheme.

Commentary by Dr. Valentin Fuster
2010;():711-718. doi:10.1115/DSCC2010-4135.

This paper presents a robust control approach to achieve an independent control authority over the intake manifold conditions of a medium-duty, V8, Diesel engine with the use of a complex air-path system. The intake manifold conditions in question include gas temperature, pressure, and oxygen mass fraction. The purpose of achieving such a high control authority over these intake manifold conditions is to explore the possibilities of extending the operating ranges of advanced combustion modes like low temperature diffusion combustion (LTDC), homogenous charge compression ignition (HCCI), and pre-mixed charge compression ignition (PCCI). Independent control of these air-path variables is made possible by using a dual-loop exhaust gas recirculation (EGR) system with a two-stage, variable geometry turbocharging (VGT) system. A multi-input-multi-output robust air-path controller was designed based on a control-oriented model identified using a high-fidelity GT-Power model of a medium-duty Diesel engine. Simulation results illustrate the effectiveness of the controller over a limited engine operating range.

Commentary by Dr. Valentin Fuster
2010;():719-726. doi:10.1115/DSCC2010-4161.

Stationary and dynamic models for the emissions of a CR-Diesel engine are developed using a global-local model approach. Results for the NOx and soot emissions are presented. All model inputs are measurable air path states and combustion parameters. They determine the emission formation before the combustion takes place. Therefore the model can be used for emission prediction and simulation. The combustion process is regarded as a batch process, such that the dynamics are introduced as external dynamics to the model via the inputs. Thus a stationary model structure can be applied. As the space of possible air path states varies widely for different engine operation points, several input and output transformations are given that linearize the input and output space. This improves the model quality and extends the operation range of the model. Modeling results are shown for stationary and dynamic data as well as for local and global model operation.

Commentary by Dr. Valentin Fuster
2010;():727-734. doi:10.1115/DSCC2010-4235.

This paper addresses the problem of simultaneous estimation of unknown state and input for a class of nonlinear systems. Under certain minimum-phase conditions, the unknown states and inputs can be recovered asymptotically with high gain observers. The design of the observer uses the perfect observation scheme such that a restrictive input-output rank condition can be relaxed. It can be shown that the proposed estimation approach of the unknown input is in the form of the integration of estimation error signals. Thanks to the integrator the common issue of measurement noise corruption of the recovered unknown inputs can be significantly reduced. The proposed approach is applied to real-time estimate in-cylinder air charge and exhaust gas recirculation (EGR) flow rate of automotive internal combustion engines which are important factors for tailpipe emission reduction.

Commentary by Dr. Valentin Fuster

Fuel Cell Modeling and Control

2010;():735-741. doi:10.1115/DSCC2010-4103.

Oxidant (air flow) control is an important aspect of fuel cell reactant control system which is designed to fulfill two purposes: air flow rate control and pressure control. These tasks require coordinated valve operation to reduce pressure variation and stabilize flow rate. In this paper, a nonlinear model describing filling dynamics of the supply and return manifolds is presented. The nonlinear model is then linearized around the stack operating point, based on which a model predictive controller is designed to maintain a constant supply and manifold pressures, as well as a constant pressure on the cathode side. Simulation studies demonstrate the model predictive controller is capable of not only regulating constant pressures during steady state operation, but also substantially reducing pressure variations during transient periods. Simulation also indicates that the control system has good robustness against model uncertainty.

Commentary by Dr. Valentin Fuster
2010;():743-750. doi:10.1115/DSCC2010-4182.

Transient control is important for prolonging the life of SOFCs and broadening their applications. This paper develops an observer based method for transient control. The essential idea is to regulate the fuel cell current using the estimated state, incorporated within a steady-state invariant property of the SOFC. The objective is to directly address hydrogen starvation in SOFCs through control of transient fuel utilization. The method is demonstrated for two different SOFC systems. The applicability across configurations indicates the possible validity of this approach for SOFCs in general. The control design is supported by simulation results.

Commentary by Dr. Valentin Fuster
2010;():751-757. doi:10.1115/DSCC2010-4239.

The water vapor transfer across a membrane exhibits non-minimum phase behavior. This paper shows that the competing dynamics of heat and mass transfer cause the membrane humidifier to have a non-minimum phase zero. Even though the non-minimum phase zero exists in the disturbance-output loop, it will limit the feedback controller gain because the disturbance-output loop is coupled with the input-output loop. The membrane properties and heat transfer parameters affect the non-minimum phase zero location. The impact on available feedback control gain and system bandwidth is analyzed in relation to changes of the non-minimum phase zero during hardware design.

Commentary by Dr. Valentin Fuster
2010;():759-765. doi:10.1115/DSCC2010-4247.

This paper discusses the development of a PEM fuel cell stack model that takes into account dynamic thermal and humidity effects. The outputs of the model are in good agreement with experimental results in literature. This nonlinear MIMO system is linearized and then analyzed by using the Relative Gain Array. The objectives are to understand the coupling between the control loops, and to pair the inputs to the outputs to achieve decentralized SISO control. The control inputs for the RGA are the compressor voltage and coolant flow rate. The performance indices are the net power output and fuel cell temperature. Analysis suggests that in most cases the stack temperature is strongly affected by the coolant flow rate, and the net power output is influenced by the compressor voltage. The coupling of the two loops is caused by the coupling of the heat and mass transfer dynamics during the fuel cell operation. When the fuel cell operates at high temperature and high current demand, the coupling of the two loops attenuates. Therefore, the decentralized SISO control is applicable when the temperature and current are high.

Commentary by Dr. Valentin Fuster
2010;():767-775. doi:10.1115/DSCC2010-4270.

This paper applies a well published control level model for fuel cell system dynamics to the unique fuel cell system of the world’s fastest fuel cell vehicle, the Buckeye Bullet 2. The goal is to develop a system model to predict the pressure dynamics of the cathode system so the cathode can be operated at maximum allowable pressure to provide maximum performance. The details of how the model must be modified to fit the unique fuel cell system are provided. The results of the initial implementation show several shortcomings when the published model is implemented. The largest problems are found to be with how the model treats the liquid product water that is generated. For this reason, modifications are implemented to attempt to improve the correlation between the model and collected data. The results show partial improvements in 3 areas of performance, indicating that more accurate dynamic models are needed to fully characterize the phenomena. Further model development and testing are planned based on the initial results.

Commentary by Dr. Valentin Fuster

Healthcare Robotics

2010;():777-783. doi:10.1115/DSCC2010-4022.

A cable-driven human assistive system has been developed to separate actuators from a human body. In the system, the assistive torque is transmitted via cables from the actuators to the end-effector which is to be attached on a human joint. The use of cables in flexible tubes allows for users to move freely without carrying the heavy actuators. However, the varying cable friction according to the curvature of the flexible tubes sets a challenge on the precise generation of the desired torque. To generate the desired torque precisely, a hierarchical control scheme is applied to the system. In this paper, the algorithms for determining the desired assistive joint torque and corresponding cable tensions are proposed. To determine the desired assistive torque, a rehabilitation strategy inspired by a potential field is discussed. For corresponding cable tensions, the algorithms for the cable tension controller which considers the varying cable friction as well as a bias for maintaining appropriate cable tensions are proposed. The performance of the proposed controller is verified by experiments.

Topics: Friction , Cables , Algorithms
Commentary by Dr. Valentin Fuster
2010;():785-791. doi:10.1115/DSCC2010-4068.

This paper describes a new electromyography (EMG) based control approach for powered above-knee prostheses. In the proposed control approach, the EMG signals are utilized as the direct control commands to the prosthesis, and thus enable the volitional control by the wearer, not only for locomotive functions, but for arbitrary motion as well. To better integrate the AK prosthesis into the rest of the human body, the control approach incorporates a human motor control mechanism-inspired ‘active-reactive’ model, which combines an active control component that reflects the wearer’s motion intention, with a reactive control component that implements the controllable impedance critical to the safe and stable interaction with the environment. The effectiveness of the proposed control approach was demonstrated through the experimental results for arbitrary free swing and level walking.

Commentary by Dr. Valentin Fuster
2010;():793-800. doi:10.1115/DSCC2010-4097.

This paper describes the mechanical design and control approach for an above-knee (AK) prosthesis actuated by pneumatic artificial muscle. Pneumatic artificial muscle (PAM) affords great potential in prosthetics, since this type of actuator features a high power density, and similar characteristics to human muscles. However, there is no application of PAM in AK prosthetics in existing literature to the best knowledge of the authors. In this paper, a design of the prosthesis is presented, which provides sufficient actuation torque for the knee joint in energy consuming locomotive functions such as fast walking and stair climbing. The corresponding control approach is also presented, which combines an impedance-based locomotive controller with a lower-level sliding-mode torque control approach. Experiments on the proposed AK prosthesis have also been conducted to demonstrate the ability to mimic normal gait characteristics.

Topics: Prostheses , Muscle , Knee
Commentary by Dr. Valentin Fuster
2010;():801-808. doi:10.1115/DSCC2010-4158.

This paper presents the development and preliminary validation of a control interface for a transfemoral prosthesis that enables EMG-based control of a powered knee during stair ascent. The approach uses results from non-amputee gait studies of stair ascent in the design of a control architecture that enables EMG modulation of knee torque in a manner biomechanically similar to that exhibited by non-amputee subjects. The myoelectric torque controller is formulated with a finite-state linear impedance model in stance and swing. The stance phase is modulated by surface EMG signals co-activated by antagonist residuum muscles. Preliminary results with a sound-limb subject using a knee immobilizer indicate that the EMG-based control architecture has the potential to enable the amputee to directly generate torque commands appropriate for stair ascent using an actively powered artificial limb.

Topics: Stairs , Prostheses
Commentary by Dr. Valentin Fuster
2010;():809-816. doi:10.1115/DSCC2010-4295.

This paper presents a life extending minimum-time path planning algorithm for legged robots, with application for a six-legged walking robot (hexapod). The leg joint fatigue life can be extended by reducing the constraint on the dynamic radial force. The dynamic model of the hexapod is built with the Newton Euler Formula. In the normal condition, the minimum-time path planning algorithm is developed through the bisecting-plane (BP) algorithm with the constraints of maximum joint angular velocity and acceleration. According to the fatigue life model for ball bearing, its fatigue life increases while the dynamic radial force on the bearing decreases. The minimum-time path planning algorithm is thus revised by reinforcing the constraint of maximum radial force based on the expectation of life extension. A symmetric hexapod with 18 degree-of-freedom is used for simulation study. As a simplified treatment, the magnitudes of dynamic radial force on proximal joints at the pair of supporting legs are set identical to achieve similar degradation rates on each joint bearing and obtain the dynamic radial force on each joint. The simulation results validate the effectiveness of the proposed idea. This scheme can extend the operating life of robot (joint bearing fatigue life) by modifying the joint path only without affecting the primary task specifications.

Topics: Robots , Path planning
Commentary by Dr. Valentin Fuster

Human/Robot Systems

2010;():817-824. doi:10.1115/DSCC2010-4003.

Several efforts have recently been made to relate the displacement of swimming three-link systems over strokes to geometric quantities of the strokes. While this approach has been successful for finding net rotations, noncommutivity concerns have prevented it from working for net translations. Our recent results on other locomoting systems have shown that the degree of this noncommutivity is dependent on the coordinates used to describe the problem, and that it can be greatly mitigated by an optimal choice of coordinates. Here, we extend the benefits of this optimal-coordinate approach to the analysis of swimming at the extremes of low and high Reynolds numbers.

Topics: Reynolds number
Commentary by Dr. Valentin Fuster
2010;():825-833. doi:10.1115/DSCC2010-4020.

This work demonstrates the autonomous command of a trained search canine to multiple waypoints using a novel state machine control algorithm. A hardware system is utilized in order to interface with the Global Position Satellite (GPS) system and with a tone and vibration generator for the purpose of accurately navigating and commanding the canine. An operational control algorithm for autonomous guidance of the canine is described in detail. Empirical results of an autonomously commanded canine are demonstrated with an 73% mission success rate for simple paths and a 62% mission success rate for complex paths. This work demonstrates a novel way to expand the capabilities of canines in a wide variety of missions, including search and detection.

Commentary by Dr. Valentin Fuster
2010;():835-842. doi:10.1115/DSCC2010-4021.

A cable-driven actuating system is proposed in this paper. The proposed system is attractive for human assistive devices because the weight of the actuator is not imposed on the human body. Since the end-effector and the actuators are connected by cables in flexible tubes, the humans are allowed to freely move in a certain range while being assisted. However, it is a challenge to account for the variable friction in the flexible tube and the inertia and friction of the actuator in the design of control algorithms. In this paper, a hierarchical control strategy is adopted to control the proposed cable-driven assistive system. To determine the reference trajectory of the motor in real-time, a sensor fusion method based on a kinematic Kalman filter with MEMS accelerometers is applied. By the proposed control methods, the proposed cable-driven system realizes a precise force-mode actuation.

Commentary by Dr. Valentin Fuster
2010;():843-850. doi:10.1115/DSCC2010-4052.

The body segment parameters (BSP) of a human body are critical information for modeling, simulating, and understanding human dynamics. The determination of BSPs of human bodies has received increasing attention in biomechanics, sport science, ergonomics, rehabilitation and other fields. This paper presents a momentum-based identification algorithm for dynamically estimating the BSPs of a human body. The human body is modeled as a multibody dynamical system, and the momentum equation of the system can be derived by applying the principle of impulse and momentum. It is possible to formulate the momentum equations corresponding to a set of experiment tests into a linear regression form with respect to the unknown BSPs, which then can be solved using the least square method or other methods. The momentum-based algorithm requires inputting position, velocity, and external force data only. Since acceleration and all the internal force data is not needed, the algorithm is less demanding on measurements and is also less sensitive to measurement errors. As a result, it is practically more appealing than the algorithms depending on the equations of motion. The paper presents the momentum-based inertia identification algorithm along with a simulation study of the algorithm using a simplified trunk-leg model representing a main portion of a human body.

Commentary by Dr. Valentin Fuster
2010;():851-858. doi:10.1115/DSCC2010-4205.

In this paper, we have determined an analytical solution for a zero-work gait for the MSU Synthetic Wheel Biped [1, 2] by choosing proper constraints. The new optimized gait ensures that the total energy of the system is the same at the beginning and the end of each step. This results in zero total work, regardless of the initial velocity of the leg or step length provided there are no losses due to friction. Furthermore, the correct choice of the gait constraints completely eliminates the ground impact forces during the foot transition. The previously developed nominal gait and the new optimized gait are implemented on a hardware prototype and a comparison of the energy consumption of these two different gait functions indicates a significant reduction in mechanical cost of transport.

Topics: Wheels
Commentary by Dr. Valentin Fuster
2010;():859-866. doi:10.1115/DSCC2010-4260.

Compliant mechanisms have the potential to increase the performance of haptic interfaces by reducing the friction and inertia felt by the user. The net result is that the user feels the dynamic forces of the virtual environment, without feeling the dynamics of the haptic interface. This “transparency” typically comes at a cost — compliant mechanisms exhibit a return-to-zero behavior that must be compensated in software. This paper presents a step toward improving the situation by using statically balanced compliant mechanisms (SBCMs), which are compliant devices that do not exhibit the return-to-zero behavior typical with most compliant mechanisms. The design and construction of a prototype haptic device based on SBCMs is presented, along with its mathematical model derived using the pseudo-rigid body model (PRBM) approach. Experimental results indicate that SBCMs effectively eliminate the return-to-zero behavior and are a feasible design element in haptic interfaces.

Commentary by Dr. Valentin Fuster

Identification and Estimation

2010;():867-874. doi:10.1115/DSCC2010-4058.

This paper presents a data-driven method of parameter identification in nonlinear systems based on the theories of symbolic dynamics. Although construction of finite-state-machine models from symbol sequences has been widely reported, similar efforts have not been expended to investigate partitioning of time series data to optimally generate symbol sequences. A data-set partitioning procedure is proposed to extract features from time series data by optimizing a multi-objective cost functional. Performance of the optimal partitioning procedure is compared with those of other traditional partitioning (e.g., uniform and maximum entropy) schemes. Then, tools of pattern classification are applied to identify the ranges of multiple parameters of a well-known chaotic nonlinear dynamical system, namely the Duffing Equation, from its time series response.

Commentary by Dr. Valentin Fuster
2010;():875-882. doi:10.1115/DSCC2010-4059.

This paper introduces a dynamic data-driven method for behavior recognition in mobile robots. The core concept of the paper is built upon the principle of symbolic dynamic filtering (SDF) that is used to extract relevant information in complex dynamical systems. The objective here is to identify the robot behavior from time-series data of piezoelectric sensor signals from the pressure sensitive floor in a laboratory environment. A symbolic feature extraction method is presented by partitioning of two-dimensional wavelet images of sensor time-series data. The K-nearest neighbors (k-NN) algorithm is used to identify the patterns extracted by SDF. The proposed method is validated by experimentation on a networked robotics test bed to detect and identify the type and motion profile of mobile robots.

Commentary by Dr. Valentin Fuster
2010;():883-889. doi:10.1115/DSCC2010-4152.

Motility is an important property of immune system cells. To describe cell motility, we use a continuous stochastic process and estimate its parameters and driving force based on a maximum likelihood approach. In order to improve the convergence of the maximization procedure, we use expectation-maximization (EM) iterations. The iterations include numerical maximization and the Kalman filter. To illustrate the method, we use cell tracks obtained from the intravital video microscopy of a zebrafish embryo.

Topics: Force
Commentary by Dr. Valentin Fuster
2010;():891-897. doi:10.1115/DSCC2010-4169.

This contribution presents a contact force estimation approach based on an optimal high-gain disturbance observer for an elastic beam using noisy measurements. The reconstruction of contact forces as an example for unknown input estimation represents a class of typical mechanical engineering problems related to the estimation of unknown effects for disturbance rejection or accommodation or fault diagnosis and isolation. The high-gain disturbance observers applied here is able to estimate estimate unknown external inputs together with system states. But choosing observer gains is a difficult task because of the influence of measurement noise. The important advantage of the proposed approach in comparison with classical high-gain disturbance observer is the self adjustment of the observer gains according to the actual estimation situation. Estimation results based on real measurements from known high-gain disturbance observer and the proposed optimal one are compared. It can be shown that the proposed algorithm allows optimized disturbance observer gains calculation, being able to be situatively adapted.

Topics: Force
Commentary by Dr. Valentin Fuster
2010;():899-906. doi:10.1115/DSCC2010-4219.

The authors apply the Adaptive High-Gain Extended Kalman Filter (AEKF) to the problem of estimating engine efficiency with data gathered from normal driving. The AEKF is an extension of the traditional Kalman Filter that allows the filter to be reactive to perturbations without sacrificing noise filtering. An observability normal form of the engine efficiency model is developed for the AEKF. The continuous-discrete AEKF is presented along with strategies for dealing with asynchronous data. Empiric test results are presented and contrasted with EKF-derived results.

Topics: Kalman filters
Commentary by Dr. Valentin Fuster
2010;():907-914. doi:10.1115/DSCC2010-4221.

This study illustrates a data driven system identification method for loudspeaker model estimation using the knowledge of the underlying physics of loudspeakers. In this study, diaphragm displacement is analyzed to estimate the model structure and parameters based on impulse response equivalent sampling and autoregressive moving average model. The estimated loudspeaker models are compared in the frequency response function plot. It is shown that the autoregressive moving average (ARMA) based loudspeaker models are comparable to the model estimated by the conventional method based on electrical impedance. Also ARMA modeling strategies with and without knowledge of the physics-based model are compared. Some issues related to ARMA modeling are addressed.

Topics: Loudspeakers
Commentary by Dr. Valentin Fuster

Marine Systems

2010;():915-922. doi:10.1115/DSCC2010-4093.

In this paper, we present the design and proof of concept of a streamlined, low-cost, and smooth-hulled underwater vehicle (MASUV-1). MASUV-1 utilizes an ad-hoc designed multi-directional thrust-vectoring system for steering and an entirely enclosed propulsion system, allowing for safe operation in the vicinity of marine mammals. Tests of the vehicle in a still water environment show high maneuverability at speeds comparable with similar torpedo-type class underwater vehicles.

Topics: Thrust , Design , Submersibles
Commentary by Dr. Valentin Fuster
2010;():923-930. doi:10.1115/DSCC2010-4098.

In this paper, we present an experimental study of gregarious fish collective behavior in the presence or absence of biomimetic vehicles. This study is aimed at developing a first understanding of fish shoal controllability using robotic exogenous mates. Macroscopic features of the group schooling are identified through laboratory experiments, conducted in a controlled environment. Experimental evidence proves the existence of qualitatively different shoal collective responses to the exogenous mate. We adapt global observables from statistical mechanics to capture the main features of the shoal collective motion, and identify possible distinct states of aggregation. Further, we investigate the effect of the exogenous mate on the shoal by using a diffusion mapping analysis performed on the global observables. The analysis shows that the exogenous mate is able to exert organizing control actions on the schooling behavior that generally result into a higher cohesion for the shoal.

Commentary by Dr. Valentin Fuster
2010;():931-937. doi:10.1115/DSCC2010-4099.

In this study, we present a class of directed graphs with bounded degree sequences, which embodies the physical phenomenon of numerosity found in the collective behavior of large animal groups. Behavioral experiments show that an animal’s perception of number is capped by a critical limit, above which an individual perceives a nonspecific “many”. This species-dependent limit plays a pivotal role in the decision making process of large groups, such as fish schools and bird flocks. Here, we consider directed graphs whose edges model information-sharing between individual vertices. We incorporate the numerosity phenomenon as a critical limit on the intake of information by bounding the degree sequence and include the variability of cognitive processes by using a random variable in the network construction. We analytically compute measures of the expected structure of this class of graphs based on cycles, clustering, and sorting among vertices. Theoretical results are verified with numerical simulation.

Topics: Networks
Commentary by Dr. Valentin Fuster
2010;():939-946. doi:10.1115/DSCC2010-4156.

The presented work addresses the output feedback control problem for a large class of uncertain nonlinear systems. The control algorithm relies on an output predictor, designed to predict the system’s measured output with arbitrary accuracy, for any admissible control signal. This output predictor is constructed using a derivative estimator, which allows the algorithm to only require limited knowledge of the system’s dynamics in general, and of the input matrix in particular. The output predictor, which is designed to be controllable, is then controlled using a backstepping control algorithm. The output feedback control problem is thus solved by controlling the predictor’s output, as opposed to controlling the actual system’s output, as is more commonly the case in the literature. Ultimately, it is shown that the predictor’s output is made to simultaneously converge to the actual system’s output and to a given desired output trajectory. It follows that the system’s output itself converges to the desired trajectory. Numerical simulation results are provided to illustrate the algorithm performance.

Commentary by Dr. Valentin Fuster
2010;():947-954. doi:10.1115/DSCC2010-4192.

We consider a time varying sensor network comprised of a group of agents equipped with communication capabilities, and we address applications where communication between agents is highly bandwidth limited as for instance in underwater missions. We use the Bayesian formalism to derive data fusion equations in which each sensor maintains an individual estimate of the state of a dynamical process. Data sharing between agents is defined by a time-varying network topology. We show that error covariances associated to estimates obtained with the independent opinion pool fusion scheme asymptotically agree if the communication network is partially asynchronous.

Commentary by Dr. Valentin Fuster
2010;():955-962. doi:10.1115/DSCC2010-4293.

This paper is concerned with the tracking control of unmanned surface vehicles. Steering dynamics is modeled using nonlinear equations with three degrees of freedom following Abkowitz. Tracking control of this nonlinear system leads to the need to derive a control algorithm for linear error equations which have time-varying coefficients. Next, a control algorithm has been derived for this set of linear time-varying equations. Lyapunov transformations have been applied to transform the error equation into a canonical form. A desired closed-loop PD-spectrum and the desired right PD-modal matrix have been chosen and the resulting Sylvester equation has been solved to obtain a matrix of time-varying controller gains. This leads to the closed loop equations for controlling the ship steering of an unmanned ship. The controller algorithm is applied to the motion control of ships with parametric values from published reports. Several tracking trajectories have been generated with and without obstacles, and time-varying control has been investigated and presented. The control algorithm is shown to be quite effective for tracking of unmanned surface vehicles. Stability conditions are derived to ensure convergence. Present work in experimental verification is outlined.

Commentary by Dr. Valentin Fuster

Micro and Nano Motion Control

2010;():963-970. doi:10.1115/DSCC2010-4124.

In this paper, an adaptive control scheme is developed to reject unknown multiple narrow-band disturbances in a hard disk drive. An adaptive notch filter is developed to efficiently estimate the frequencies of the disturbance. Based on the correctly estimated parameters, a disturbance observer with a newly designed multiple band-pass filter is constructed to achieve asymptotic perfect rejection of the disturbance. Evaluation of the control scheme is performed on a benchmark problem for HDD track following.

Topics: Disks , Filters
Commentary by Dr. Valentin Fuster
2010;():971-978. doi:10.1115/DSCC2010-4133.

This paper presents a novel Ackermann-like eigenvalue assignment control architecture for a linear time-varying system in the presence of time-varying disturbances. Eigenvalue assignment architectures are presented as a way to achieving feedback stabilization. This method does not require the transformation of the original system into a phase-variable canonical form nor the computation of the PD-eigenvalue of the original system. An example is given to demonstrate the performance of this proposed control method.

Commentary by Dr. Valentin Fuster
2010;():979-986. doi:10.1115/DSCC2010-4153.

Prototyping and fabrication of nanodevices require subnanometer tolerances and highly accurate sensing and actuation. Improved control on manipulating matter at the nanoscale is of relevance in different fields such as the automotive industry, biotechnology and communication. Limitations of existing nanomanipulation systems include constrained motion of manipulator end-effectors. In the present paper, a new AFM probe design suitable for nanomanipulation is proposed. The design includes a nanomanipulation piezotube that allows actuation and sensing of the tip motion in three directions. In addition, a piezopatch is attached to the cantilever holder for in-situ stiffness tuning needed for manipulating large and sticky nanosamples. Design considerations and path tracking performance of the proposed manipulator are analyzed.

Commentary by Dr. Valentin Fuster
2010;():987-992. doi:10.1115/DSCC2010-4163.

This paper proposes a new design procedure for track-following control systems in hard disk drives. The procedure is automated, in the sense that, for given experimental frequency response data of the suspension arm dynamics and a model structure, it automatically derives a transfer function set with uncorrelated parametric uncertainties. Subsequently, for the transfer function set, a given controller structure, and closed-loop performance specifications in the frequency domain, it automatically designs a partition of the uncertainties and corresponding multiple robust controllers. Experiments on actual hard disk drives demonstrate the usefulness and efficiency of the proposed procedure.

Commentary by Dr. Valentin Fuster
2010;():993-1000. doi:10.1115/DSCC2010-4285.

This paper discusses optimal H∞ control synthesis via discrete Riccati equations for discrete linear periodically time-varying (LPTV) systems. Based on the results presented in [1], an explicit minimum entropy H∞ controller for general time-varying systems is obtained. The control synthesis technique is subsequently applied to LPTV systems and it is shown that the resulting controllers are also periodically time varying. In order to demonstrate the effectiveness of the proposed control synthesis technique, both single-rate and multi-rate discrete-time minimum entropy H∞ track-following control designs for hard disk drives are considered. It is shown, via a comprehensive simulation study, that track-following controllers designed using the H∞ synthesis technique proposed in this paper achieve the robust performance of a desired error rejection function. Moreover, as expected, multi-rate controllers has the ability of outperforming their single-rate counterparts.

Commentary by Dr. Valentin Fuster

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In