ASME Conference Presenter Attendance Policy and Archival Proceedings

2014;():V001T00A001. doi:10.1115/DSCC2014-NS1.

This online compilation of papers from the ASME 2014 Dynamic Systems and Control Conference (DSCC2014) represents the archival version of the Conference Proceedings. According to ASME’s conference presenter attendance policy, if a paper is not presented at the Conference, the paper will not be published in the official archival Proceedings, which are registered with the Library of Congress and are submitted for abstracting and indexing. The paper also will not be published in The ASME Digital Collection and may not be cited as a published paper.

Commentary by Dr. Valentin Fuster

Advances in Active Control of Aerospace Structure

2014;():V001T01A001. doi:10.1115/DSCC2014-5886.

Tensegrity-membrane systems are deployable structures that can be utilized in space applications such as solar sails and radar systems. This work addresses the control design for four-bar tensegrity-membrane systems. The tendons act as actuators, and the system can be controlled by changing the rest-lengths of the tendons. Lagrange’s method is used to model the system, and the equations of motion are expressed as a set of differential-algebraic equations (DAE). For control design, the equations of motion of the system in the DAE form are converted into the form of second order ordinary differential equations based on coordinate partitioning and coordinate mapping. Since the number of control inputs is less than the number of state variables, these systems can be classified as underactuated nonlinear systems. The collocated partial feedback linearization (PFL) technique is implemented to design a nonlinear controller. Simulation results of the closed-loop system under initial perturbation are presented, and the performance of the controller is discussed.

Topics: Membranes , Tensegrity
Commentary by Dr. Valentin Fuster
2014;():V001T01A002. doi:10.1115/DSCC2014-6204.

A Linear Particle Chain (LPC) impact damper is a newly developed passive vibration control device. It is an extension for the commonly used conventional (single unit) impact damper. In this paper, experimental investigations are conducted to examine the efficacy of the LPC impact damper in attenuating the free vibrations of single degree of freedom structures. The experiments’ outcomes clearly indicate the significant effect of the LPC impact damper in suppressing the structure vibration compared to the conventional impact dampers.

Commentary by Dr. Valentin Fuster
2014;():V001T01A003. doi:10.1115/DSCC2014-6294.

This paper presents an active flutter suppression design using linear parameter-varying (LPV) control method for a nonlinear aeroservoelastic model that captures wing-section stall flutter. The loss-of-effectiveness fault is considered for the control surface. The resulting model is a function of speed as well as effectiveness factor of the control surface. These two parameters are treated as the varying parameters to formulate an LPV representation of the wing-section model using Jacobian linearization. An H2 gain-scheduled controller based on a parameter-dependent Lyapunov function is designed for the LPV system. The simulation shows that it can suppress limit cycle oscillations over a range of speed and work under a certain range of control surface effectiveness loss.

Commentary by Dr. Valentin Fuster
2014;():V001T01A004. doi:10.1115/DSCC2014-6337.

Following the current trend in aeroelastic optimization, as wing structures have been made more flexible, active control systems such as flutter suppression systems have been widely adopted to reduce undesirable aeroelastic behaviors. The stability and the performance of flutter suppression control systems can be negatively affected as the inflow speed deviates from the nominal design value. In this work, a mixed-norm robust controller is designed to perform stall flutter suppression. A 2-dimensional nonlinear time-domain aeroservoelastic model is developed. The nonlinear equations are linearized at different flight conditions and are employed to construct an uncertainty model, which affects the nominal dynamics in an affine way. The obtained uncertain model of the aeroservoelastic system is used to design a mixed-norm H2/H controller. The performance of the designed controller is compared with the performance of a non-robust H2 controller at different flight conditions. The proposed control architecture reduces the adverse effect of inflow speed variation on the performance of the closed-loop system.

Commentary by Dr. Valentin Fuster

Advances in Motion Control

2014;():V001T02A001. doi:10.1115/DSCC2014-5846.

Arduino microcontrollers are popular, low-cost, easy-to-program, and have an active user community. This paper seeks to quantitatively assess whether or not Arduinos are a good fit for real-time feedback control experiments and controls education. Bode plots and serial echo tests are used to assess the use of Arduinos in two scenarios: a prototyping mode that involves bidirectional real-time serial communication with a PC and a hybrid mode that streams data in real-time over serial. The closed-loop performance with the Arduino is comparable to that of another more complicated and more expensive microcontroller for the plant considered. Some practical tips on using an Arduino for real-time feedback control are also given.

Commentary by Dr. Valentin Fuster
2014;():V001T02A002. doi:10.1115/DSCC2014-5962.

In this paper, an interactive robotic anthropomorphic hand system is presented, which was developed as an important tool for the educational outreach activities. The robotic anthropomorphic hand incorporates 15 degrees of freedom, providing sufficient mobility in the demonstration of various postures. To increase the attractiveness of the robotic hand, pneumatic muscle actuators are used to drive the robotic hand motion through artificial tendons. The interaction of the robotic hand with a human is enabled with a control device, which allows the human operator to control the hand motion in a natural way. The robotic hand system has been successfully demonstrated in a recent engineering education outreach event, in which over 100 children at all ages operated the robotic hand through the control device.

Topics: Robotics , Education
Commentary by Dr. Valentin Fuster
2014;():V001T02A003. doi:10.1115/DSCC2014-6039.

Time optimal trajectory planning under various hard constraints plays a significant role in simultaneously meeting the requirements on high productivity and high accuracy in the fields of both machining tools and robotics. In this paper, the problem of time optimal trajectory planning is first formulated. A novel back and forward check algorithm is subsequently proposed to solve the minimum time feed-rate optimization problem. The basic idea of the algorithm is to search the feasible solution in the specified interval using the back or forward operations. Four lemmas are presented to illustrate the calculating procedure of optimal solution and the feasibility of the proposed algorithm. Both the elliptic curve and eight profile are used as case studies to verify the effectiveness of the proposed algorithm.

Commentary by Dr. Valentin Fuster
2014;():V001T02A004. doi:10.1115/DSCC2014-6046.

The aim of this research is to expand the possibilities of multi-disciplinary controls education at the undergraduate and graduate levels with an affordable laboratory kit. A kit was assembled for around $130 while replicating the educational functionality of a typical laboratory station in a university controls laboratory. This kit could also replace expensive equipment with an affordable alternative that can be easily shipped anywhere in the world and used by students with any computer. This greatly enhances the accessibility of the laboratory experience to students in budget-strapped campus laboratories and those participating in distance education. The kit design consists of a Raspberry Pi, a DC motor, and various components required for the lab exercises. The first two kits allow students to complete labs that include DC motor system identification, DC motor control, inverted pendulum control, and any other project a student might want to create with a Raspberry Pi, DC motor, and a 3-D printer.

Commentary by Dr. Valentin Fuster
2014;():V001T02A005. doi:10.1115/DSCC2014-6114.

Dual-stage positioning systems have been widely used in factory automation, robotic manipulators, high-density data storage systems, and manufacturing systems. Trajectory generation and control of dual-stage positioning systems is of great importance and is made complicated by the presence of physical and operational constraints. In this work, we describe how to generate feasible reference trajectories for a dual-stage positioning system consisting of a fine stage and a coarse stage, and how to use them in a model predictive control algorithm for which recursive feasibility is guaranteed. The reference generation algorithm is guaranteed to generate trajectories that satisfy all the constraints for the fine and coarse stages. We also describe a constrained model predictive control algorithm used to control the coarse stage. The simulation results of applying the developed methodology to track a pre-determined pattern is presented.

Commentary by Dr. Valentin Fuster
2014;():V001T02A006. doi:10.1115/DSCC2014-6202.

This paper investigates the problem of rapidly transitioning the pose of a limbed robot while remaining balanced. In particular, we consider motions where rotational accelerations may significantly affect the center of pressure location within a limited base of support. We consider solutions for high-impedance robots with stiff, high-torque actuators that essentially provide accurate, position-control outputs at the joints. We present and compare three methods for generating joint trajectories to achieve fast yet feasible dynamic motions for such systems while maintaining a safety margin for the center of pressure location, toward robust balance. We focus on development of theory and intuition for each method and quantify performance in terms of achievable speed of transition and required joint velocity limits.

Commentary by Dr. Valentin Fuster

Aerospace Control Applications

2014;():V001T03A001. doi:10.1115/DSCC2014-5890.

This paper presents the development and testing of a novel fault tolerant adaptive control system based on a bio-inspired immunity-based mechanism applied to an aircraft fighter model. The proposed baseline control laws use a non-linear dynamic inversion and model reference adaptive control on the inner loops of the aircraft dynamics. In this new approach, the baseline controllers are augmented with an artificial immune system mechanism that relies on a direct compensation inspired primarily by the biological immune system response. The effectiveness of the approach is demonstrated through a full 6 degrees-of-freedom aircraft model interfaced with a Flight gear environment. The performance of the proposed control laws are investigated under a novel set of performance metrics, which quantify the level of input activity from the pilot and from the control surfaces in order to ensure the stability and performance of the aircraft under different actuator and structural failures. Optimization of the parameters of the artificial immunity system is performed using a genetic algorithm. The results show that the optimized fault tolerant adaptive control laws improve significantly the failure rejection using minimum pilot input and control surfaces activity under upset flight conditions.

Commentary by Dr. Valentin Fuster
2014;():V001T03A002. doi:10.1115/DSCC2014-5894.

A pointing control system is developed for the Gamma-Ray Imager/Polarimeter for Solar flares (GRIPS) balloon-borne instrument which provides a near-optimal combination of high-resolution imaging, spectroscopy, and polarimetry of solar-flare gamma-ray/hard X-ray emissions from ∼20 keV to ∼10 MeV. Within the narrow field of view of its sun sensor, the telescope must track the sun with a 0.5 degrees rms accuracy. This paper introduces the mechanical structure of the pointing control system and investigates the dynamics and control strategy and presents the simulation and experimental results.

Commentary by Dr. Valentin Fuster
2014;():V001T03A003. doi:10.1115/DSCC2014-5895.

CINEMA (CubeSat for Ions, Neutrals, Electrons and MAgneticfields) will image energetic neutral atoms (ENAs) in the magnetosphere, and make measurements of electrons, ions, and magnetic fields at high latitudes. To satisfy the mission requirements, the three unit cubesat was designed. The spin axis needs to be in the ecliptic normal and the spin rate needs to be 4 rpm. The only power source for CINEMA is the solar panels. External torques are generated by an orthogonal pair of coils acting with the earths magnetic field. This paper provides the control strategy, given the limited power and available sensors, to optimize the convergence of the spin and attitude control.

Commentary by Dr. Valentin Fuster
2014;():V001T03A004. doi:10.1115/DSCC2014-5899.

This paper describes the design, development, and flight-simulation testing of an artificial immune-system-based approach for accommodation of different aircraft sub-system failures/damages. The accommodation of abnormal flight conditions is regarded as part of a complex integrated artificial immune system scheme, which consists of four major components: detection, identification, evaluation, and accommodation. The accommodation part consists of providing compensatory commands under upset conditions for specific maneuvers.

The approach is based on building an artificial memory, which represents the self (nominal conditions) and the non-self (abnormal conditions) within the artificial immune system paradigm. Self and non-self are structured as a set of memory cells consisting of measurement strings, over pre-defined time windows. Each string is a set of features values at each sample time of the flight including pilot inputs, system states, and other variables. The accommodation algorithm is based on the cell in the memory that is the most similar to the in-coming measurement. Once the best match is found, control commands corresponding to this match will be extracted from the memory and used for control purposes.

The proposed methodology is illustrated through simulation of simple maneuvers at nominal flight conditions and under locked actuator.

The results demonstrate the possibility of extracting pilot compensatory commands from the self/non-self structure and capability of the artificial-immune-system-based scheme to accommodate an actuator malfunction, maintain control, and complete the task.

Topics: Aircraft , Failure
Commentary by Dr. Valentin Fuster
2014;():V001T03A005. doi:10.1115/DSCC2014-6047.

An adaptive regulator is designed for parameter dependent families of systems subject to changes in the zero structure. Since continuous adaptive regulation is limited by relative degree and right half plane zeros, a multiple model adaptive regulator is implemented. The two multiple model design subproblems, covering and switching, are addressed with LQR state feedback and Lyapunov function switch logic respectively. These two subproblems are combined into a set of Linear Matrix Inequalities (LMI) and concurrently solved. The multiple model design method is applied to longitudinal aircraft dynamics.

Commentary by Dr. Valentin Fuster

Assistive Robotic Systems

2014;():V001T04A001. doi:10.1115/DSCC2014-5963.

Amputee locomotion can benefit from recent advances in robotic prostheses, but their control systems design poses challenges. Prosthesis control typically discretizes the nonlinear gait cycle into phases, with each phase controlled by different linear controllers. Unfortunately, real-time identification of gait phases and tuning of controller parameters limit implementation. Recently, biped robots have used phase variables and virtual constraints to characterize the gait cycle as a whole. Although phase variables and virtual constraints could solve issues with discretizing the gait cycle, the virtual constraints method from robotics does not readily translate to prosthetics because of hard-to-measure quantities, like the interaction forces between the user and prosthesis socket, and prosthesis parameters which are often altered by a clinician even for a known patient. We use the simultaneous stabilization approach to design a low-order, linear time-invariant controller for ankle prostheses independent of such quantities to enforce a virtual constraint. We show in simulation that this controller produces suitable walking gaits for a simplified amputee model.

Topics: Prostheses
Commentary by Dr. Valentin Fuster
2014;():V001T04A002. doi:10.1115/DSCC2014-6145.

A significant market need has been identified for an improved assist device for transferring mobility limited patients, particularly those who are heavier or bariatric. This paper discusses our needs assessment for a new patient transfer assist device (PTAD), an initial design for a multiple degree of freedom hydraulically actuated device, and possible solutions for the caretaker interface design. The relevant patient population includes those with spinal cord injuries, neuromuscular disorders, and the elderly; most patients are wheelchair users and unable to perform independent transfers. The caretaker interface design for the PTAD presents a unique challenge in terms of human-machine collaborative manipulation, as well as control of a powerful and intrinsically stiff machine in a delicate environment with both the caretaker and patient in the workspace. This paper presents a needs assessment to determine the specific problems with the antiquated current market patient lifts, as well as user input on proposed improvements. It also presents the design of a functional first prototype PTAD, a mechanical simulation, preliminary simulation results on an impedance control approach, and next steps toward design and implementation of a caretaker- and patient-friendly operator interface and control system.

Topics: Machinery
Commentary by Dr. Valentin Fuster
2014;():V001T04A003. doi:10.1115/DSCC2014-6161.

To achieve automatic operation of a powered orthosis-aided gait or functional electrical stimulation-based walking restoration, accurate estimation of the leg angles is of utmost importance. Various phases of walking last for a short duration of time; thus, an accurate estimator is required with a fast convergence rate. To overcome this challenge, this paper presents a discrete-time nonlinear estimation algorithm to estimate lower-limb angles during an orthosis-aided walking. To this end, we use measurements from 6 degree-of-freedom (DOF) inertial measurement units (IMUs) to estimate the lower limb angles. The estimator is based on a state-dependent coefficient (SDC) linearization or extended linearization of the nonlinear functions. A combination of multiple discrete SDCs is used to compute an optimal gain of the nonlinear estimator based on uncertainty minimization criteria. The nonlinear estimator is robust to uncertainties in system modeling and sensor noise/bias from the IMUs. Monte Carlo simulation studies reveal that the estimator outperforms widely used discrete-time extended Kalman (EKF) filter with respect to average root-mean squared estimation error (RMSE) criteria.

Topics: Orthotics
Commentary by Dr. Valentin Fuster
2014;():V001T04A004. doi:10.1115/DSCC2014-6184.

Shoe-floor interactions such as friction force and deformation/local slip distributions are among the critical factors to determine the risk for potential slip and fall. In this paper, we present modeling, analysis, and experiments to understand the slip and force distributions between the shoe sole and floor surface during the normal gait and the slip and fall gait. The computational results for the slip and friction force distribution are based on the spring-beam networks model. The experiments are conducted with several new sensing techniques. The in-situ contour footprint is accurately measured by a set of laser line generators and image processing algorithms. The force distributions are obtained by combining two types of force sensor measurements: implanted conductive rubber-based force sensor arrays in the shoe sole and six degree-of-freedom (6-DOF) insole force/torque sensors. We demonstrate the sensing system development through extensive experiments. Finally, the new sensing system and modeling framework confirm that the use of required coefficient of friction and the deformation measurements can real-time predict the slip occurrence.

Topics: Modeling
Commentary by Dr. Valentin Fuster
2014;():V001T04A005. doi:10.1115/DSCC2014-6201.

This work addresses the problem of resolving kinematic redundancy in legged robots, with the dual goals of maintaining a large reachable workspace and of achieving fast end effector motions in task space. In particular, for robots with four or more legs, gait planning allows for considerable flexibility in the orientation of a stance limb with respect to both body orientation and the ground. By appropriately commanding pitch, roll and yaw of the end effector as it moves relative to the body coordinate frame, one can increase the volume of space the feet can reach and thus allow the robot to negotiate larger terrain obstacles. At the same time, motions of the foot in task space should be done rapidly, given the joint velocities of the limbs. In this paper, we focus on RoboSimian, a robot with four identical limbs designed for dual use in manipulation and locomotion tasks, which was designed at Jet Propulsion Labs (JPL) for the DARPA Robotics Challenge (DRC). We present both heuristic guidelines and a novel, gradient-based algorithm for developing rules to set the inverse kinematics (IK) solution for the seven joint angles of a limb, allowing us to prescribe joint solutions rapidly through the use of an IK look-up table.

Commentary by Dr. Valentin Fuster
2014;():V001T04A006. doi:10.1115/DSCC2014-6215.

A majority of stroke patients suffer from the loss of effective motor function, which compromises their ability to control grasping motion. Hand rehabilitation is therefore important to improve their motor function and quality of life in activities of daily living (ADLs). In this initial work, we present the design and development of a partial hand exoskeleton actuated by shape memory alloy (SMA) spring actuators. The SMA spring actuators are cooled by forced convection and the individual joints of the finger are actuated via tendons. In this design, pre-tension in the passive springs enables the restoration of the original configuration when the SMA springs are not actuated. To address the slow cooling rate of SMA springs that limits the control performance, we developed a cooling unit for each SMA spring actuator. We utilized computer vision to identify an object and provide 3-D coordinates of the optimal grasping points on the object. We then utilized vision-based control to move the fingertips towards the grasping points. The experimental results showed that each individual joint was able to return to its original configuration significantly faster as well as to follow a sinusoidal trajectory with the proposed cooling strategy.

Commentary by Dr. Valentin Fuster

Bio-Inspired Systems

2014;():V001T05A001. doi:10.1115/DSCC2014-5885.

Based on the artificial immune system paradigm and a hierarchical multi-self strategy, a set of algorithms for aircraft sub-systems failure detection, identification, evaluation and flight envelope estimation have been developed and implemented. Data from a six degrees-of-freedom flight simulator were used to define a large set of 2-dimensional self/non-self projections as well as for the generation of antibodies and identifiers designated for health assessment of an aircraft under upset conditions. The methodology presented in this paper classifies and quantifies the type and severity of a broad number of aircraft actuators, sensors, engine and structural component failures. In addition, the impact of these upset conditions on the flight envelope is estimated using nominal test data. Based on immune negative and positive selection mechanisms, a heuristic selection of sub-selves and the formulation of a mapping-based algorithm capable of selectively capturing the dynamic fingerprint of upset conditions is implemented. The performance of the approach is assessed in terms of detection and identification rates, false alarms, and correct prediction of flight envelope reduction with respect to specific states.

Commentary by Dr. Valentin Fuster
2014;():V001T05A002. doi:10.1115/DSCC2014-6076.

Current models for multi-agent systems almost exclusively employ sensory modalities such as vision where agents passively receive information from the environment. Active sensing, defined as acquiring environmental information using self-generated signals, allows widespread sharing of sensory information among agents and thus gives rise to more complex interactions within engineered multi-agent systems using radar or sonar, for example. In nature, bat swarms are animal groups that successfully employ active sensing with each individual broadcasting echolocation pulses in the environment and responding to echoes. Bats flying in groups may cope with the dense sound environment through their behavior; one hypothesized strategy is the cessation of echolocation pulses in the presence of peers and “eavesdropping”, which has been demonstrated in controlled laboratory settings. In this work, we build a self-propelled-particle model with each agent avoiding obstacles in three dimensions by emitting echolocation pulses of a unique frequency. We implement a bat-inspired rule of eavesdropping to take advantage of information sharing via active sensing while reducing the energy expenditure of the group. Through a simulation study, we show that agents indeed capitalize on peers’ pulses and echoes for obstacle avoidance and we find a maximum of this effect for a set of model parameters which relate to the domain size.

Commentary by Dr. Valentin Fuster
2014;():V001T05A003. doi:10.1115/DSCC2014-6141.

In this paper, we develop a framework for evolution of a multi agent systems (MAS) under local perception. The idea of this paper comes from natural biological swarms where agents adjust their behavior based on individual perception of the behavior of its neighbors. Most available engineered swarms rely on local communication where an individual agent needs exact state information of its adjacent agents to evolve. We consider agents of a MAS to be particles of a continuum (deformable Body) transforming under a homogenous mapping. Homogenous transformations have the property that two crossing straight lines in an initial configuration translate as two different crossing straight lines. We will consider this feature of homogenous mappings to show how certain desired objectives can be achieved by agents of a swarm by preserving alignment among nearby agents. We show that evolution of a MAS under this alignment strategy can be achieved where agents don’t need to know the exact positions of the adjacent agents nor do they need peer to peer communication.

Commentary by Dr. Valentin Fuster
2014;():V001T05A004. doi:10.1115/DSCC2014-6219.

Aerial pursuit in nature is a complex task that involves interaction with targets in motion. To date, many researchers have analyzed aerial predation strategies used by different flying species for the pursuit and interception of targets such as a prey or a conspecific. In this article, we provide a brief review of these different predation strategies with the focus primarily on insects and bats that rely on different sensory variables (vision and sonar) for navigation. The Knowledge gained from studying these strategies can guide the development of bio-inspired approaches for navigation of engineered systems.

Commentary by Dr. Valentin Fuster
2014;():V001T05A005. doi:10.1115/DSCC2014-6265.

In this paper, we propose a novel design for a pectoral fin joint of a robotic fish. This joint uses a flexible part to enable the rowing pectoral fin to feather passively and thus reduce the hydrodynamic drag in the recovery stroke. On the other hand, a mechanical stopper allows the fin to maintain its motion prescribed by the servomotor in the power stroke. The design results in net thrust even when the fin is actuated symmetrically for the power and recovery strokes. A dynamic model for this joint and for a pectoral fin-actuated robotic fish involving such joints is presented. The pectoral fin is modeled as a rigid plate connected to the servo arm through a pair of torsional spring and damper that describes the flexible joint. The hydrodynamic force on the fin is evaluated with blade element theory, where all three components of the force are considered due to the feathering degree of freedom of the fin. Experimental results on robotic fish prototype are provided to support the effectiveness of the design and the presented dynamic model. We utilize three different joints (with different sizes and different flexible materials), produced with a multi-material 3D printer, and measure the feathering angles of the joints and the forward swimming velocities of the robotic fish. Good match between the model predictions and experimental data is achieved, and the advantage of the proposed flexible joint over a rigid joint, where the power and recovery strokes have to be actuated at different speeds to produce thrust, is demonstrated.

Commentary by Dr. Valentin Fuster

Biomedical and Bioengineering Applications

2014;():V001T06A001. doi:10.1115/DSCC2014-5864.

In this paper, we analyze the problem of stabilizing a rotating eye movement control system satisfying the Listing’s constraint. The control system is described using a suitably defined Lagrangian and written in the corresponding Hamiltonian form. We introduce a damping control and show that this choice of control asymptotically stabilizes the equilibrium point of the dynamics, while driving the state to a point of minimum total energy. The equilibrium point can be placed by appropriately locating the minimum of a potential function. The damping controller has been shown to be optimal with respect to a suitable cost function. We choose alternate forms of this cost function, by adding a term proportional to the potential energy, and synthesize stabilizing control, using numerical solution to the the well known Hamilton Jacobi Bellman equation. Using Chebyshev collocation method, the newly synthesized controller is compared with the damping control.

Commentary by Dr. Valentin Fuster
2014;():V001T06A002. doi:10.1115/DSCC2014-6084.

A Ventricular Assistive Device (VAD) is a mechanical pump used to assist the functioning of a weak heart. A catastrophic obstruction in the VAD system could cost the patient their life. This paper discusses a fault detection approach using the commercially available Jarvik 2000 Flowmaker® VAD in a closed loop circuit that incorporates the ability to alter common causes of VAD congestion. Principal Component Analysis, a data compression technique used to discover patterns in data of high dimension, is implemented using frequency analysis of the VAD’s acoustic signature. This is followed by a health classification based on Bayes theorem. The classification results indicate that this technique is accurate to a high degree in detecting three levels of obstruction in the VAD system.

Commentary by Dr. Valentin Fuster
2014;():V001T06A003. doi:10.1115/DSCC2014-6268.

The work presented here details the development of a wireless instrumentation architecture for direct gait measurement in a transfemoral prosthesis. The system comprises a pair of multi-axis load cells located proximal to the ankle and knee joints of the prosthesis that provide a measure of moments and axial force above and below the prosthetic knee. The kinetic measurements are supplemented with knee kinematics measured using a modular goniometer attached lateral to the prosthetic knee and ground contact as indicated with a pneumatic sensor at the prosthetic heel. Each instrument wirelessly transmits collected data to host PCs, enabling direct gait measurements free of the constraints of a conventional gait laboratory setting. The data acquisition system was evaluated with a single subject with unilateral transfemoral amputation walking with a polycentric knee, composite energy-return foot, and daily-use socket. Experimental results were collected for the subject walking through a theater, enabling the rapid acquisition of gait data for level-ground walking and incline ascent/descent without the need for a motion-capture camera array or floor-embedded force plates.

Topics: Prostheses
Commentary by Dr. Valentin Fuster
2014;():V001T06A004. doi:10.1115/DSCC2014-6297.

pNN50 is a metric derived from heart rate (HR) measurements, and it is known to correlate with mental-workload changes in human subjects. Conventionally, this metric is calculated based on the variability of successive time periods in peak-to-peak occurrences in HR data. In the case of noisy measurements of HR, however, peak-to-peak detection may not be reliable. Here, we present a combined time-frequency domain analysis, benefiting from Short Time Fourier Transform, by which we can more accurately extract pNN50 metric from noisy HR data. An experimental measurement with added noise is used as a benchmark problem to demonstrate the effectiveness of the approach with noticeable improvement over the conventional time domain peak-to-peak detection algorithm.

Commentary by Dr. Valentin Fuster
2014;():V001T06A005. doi:10.1115/DSCC2014-6324.

This paper addresses the problem of motion tracking of human skeleton system using non-invasive vision based sensors. The proposed approach combines synergistic paradigms of image processing, kinematics of rigid bodies and Extended Kalman Filtering scheme to estimate the motion of a human limb system. This approach solely depends on the measurement obtained from the vision sensors without involving any wearable or inertial sensors to measure the motion parameters. In this paper we propose fusion of two filtering schemes — the optical flow equations applied to raw images obtained from the Microsoft Kinect and extended Kalman filter for human skeleton considered as a system of kinematic linkages. The strategy proposed in this paper yields near optimal results as is demonstrated with the help of experiments performed using the Microsoft Kinect sensor and compared using accurate tracks obtained from 24-Camera Optitrack motion capture system.

Commentary by Dr. Valentin Fuster
2014;():V001T06A006. doi:10.1115/DSCC2014-6354.

It is well known that obesity, a chronic disease, can lead to increased risk of other serious chronic diseases and even death. Knowledge of daily changes in lean muscle mass and body fat can be helpful in developing personalized diet and exercise routines to correct this problem. In this paper, it is assumed that measurements of individual body composition components are available only periodically although the total body weight is tracked on a daily basis. The control input is physical activity whose profile can be constrained to accommodate individual preferences while the energy intake can be arbitrary. We present switching and time delayed feedback based model-free control methods for the dynamic management of body mass and its major components. Additionally, based on human body weight dynamics, estimation of body composition using soft switching-based observer is proposed. Simulation results validate the performance of the proposed controllers and the observer under disturbances in recording energy intake and energy expenditure figures.

Topics: Weight (Mass) , Design
Commentary by Dr. Valentin Fuster

Building Energy Systems

2014;():V001T07A001. doi:10.1115/DSCC2014-6051.

Commercial demand response (DR) has traditionally relied on HVAC and lighting systems as load-shed resources in buildings. However, improvements in technologies such as Energy Information Gateways and smart power strips are making it possible to incorporate distributed plug-loads as an actionable resource. In this paper we explore the addition of a battery storage system (BSS) as a load-shed resource to supplement plug-loads in an office setting. Furthermore we investigate the value of control of BSS battery charging. We develop a model predictive control (MPC) framework for office plug-loads and a BSS. An experimentally derived model of a BSS is presented along with numerical methods for solving the MPC optimization program. Simulations demonstrate the efficacy of a BSS as a load-shed resource. Simulation results also quantify the benefit of BSS controllable charging for DR and load-following scenarios.

Commentary by Dr. Valentin Fuster
2014;():V001T07A002. doi:10.1115/DSCC2014-6134.

Model based control has been proven to have significant building energy saving potentials through operation optimization. Accurate and computationally efficient, and cost-effective building energy model are essential for model based control. Existing studies in this area have mostly been focusing on reducing computation burden using simplified physics based modeling approach. However, creating and identification the simplified physics based model is often challenging and requires significant engineering efforts. Therefore, this study proposes a novel methodology to develop building energy estimation models for on-line building control and optimization using an integrated system identification and data fusion approach. System identification model has been developed based on frequency domain spectral density analysis. Eigensystem realization algorithm is used to generate the state space model from the Markov parameters. Kalman filter based data fusion technique has also been implemented to improve the accuracy and robustness of the model by incorporating with real measurements. A systematic analysis of system structure, system excitation selection as well as data fusion implementation is also demonstrated. The developed strategies are evaluated using a simulated testing building (simulated in EnergyPlus environment). The overall building energy estimation accuracy from this proposed model can reach to above 95% within 2 minutes calculation time, when compared against detailed physics based simulation results from the EnergyPlus model.

Commentary by Dr. Valentin Fuster
2014;():V001T07A003. doi:10.1115/DSCC2014-6152.

The class of buildings designated as commercial is comprised of many different architectures and functions, which presents a challenge when developing demand management strategies that are applicable across this field. Most advanced controllers are based on a model of the thermal loads in the building envelope. These models do not directly extrapolate to measures of power consumption, which is what building owners are ultimately interested in managing. In this work, we develop models of power use that can be easily tailored to model power demand in any commercial building with advanced sensing and metering. We address how existing models of the building temperature states can be incorporated into our framework. Specifically, we show how Auto-Regressive models with eXogeneous (ARX) inputs can be used for superior day-ahead forecasting of demand, and how to formulate the models in a way that is meaningful at the supervisory level. These models provide more flexibility in the design of a supervisory controller for building energy management and the information they provide is crucial for bridging the gap between buildings and utilities in the smart grid.

Commentary by Dr. Valentin Fuster
2014;():V001T07A004. doi:10.1115/DSCC2014-6163.

State-of-the-Art feedback control of lighting depends on point sensor measurements for light field generation. However, since the occupant’s perception depends on the entire light field in the room instead of the illumination at a limited set of points, the performance of these lighting control systems may be unsatisfactory. Therefore, it is critical to reconstruct the light field in the room from point sensor measurements and use it for feedback control of lights. This paper presents a framework for using graphical rendering tools along with point sensor measurements for the estimation of a light field and using these estimates for feedback control. Computer graphics software is used to efficiently and accurately model building spaces, while a game engine is used to render different lighting conditions for the space on the fly. These real-time renderings are then used together with sensor measurements to estimate and control the light field in the room using an optimization-based feedback control approach. We present a set of estimation algorithms for this purpose and analyze their convergence and performance limitations. Finally, we demonstrate closed loop lighting control systems that use these estimation algorithms and compare their relative performance, highlighting their benefits and disadvantages.

Topics: Engines , Rendering
Commentary by Dr. Valentin Fuster
2014;():V001T07A005. doi:10.1115/DSCC2014-6224.

Model predictive control (MPC) offers a tremendous scope in optimizing the consumption of energy by building HVAC systems. This paper presents an automated real-time procedure for the development of linear parametric models of building air-conditioning systems through system identification for the implementation of the MPC algorithms. The procedure is used to decide on the various aspects of system identification such as selecting the model structure, the inputs to the system, the interaction of the systems with their neighbors, and the updating of the model coefficients in real-time. The effectiveness of the procedure is demonstrated by modeling the various components air-conditioning systems of a real building. The root mean squared error was used as a performance metric to gauge the models. The paper also demonstrates that a 15 minute sampling interval is sufficient to model the dynamics of the air-handling unit and the room temperatures, but a faster sampling rate may be required to model the VAV boxes.

Commentary by Dr. Valentin Fuster

Condition Based Monitoring

2014;():V001T08A001. doi:10.1115/DSCC2014-5928.

This paper presents the implementation of a new adaptation algorithm to model the crack propagation of roller bearings and to predict their Remaining Useful Life (RUL). The developed algorithm is designed based on the adaptive auto-step reinforcement-learning method combined with a crack propagation model. The advantage of this algorithm is that it is now able to not only estimate the defect growth rate online, but also to predict the RUL of a roller bearing element. The presented defect propagation model incorporated in this work is an extension to the Paris’s formula that is well known in the fracture mechanics community. Further, a new adaptive filtering technique, referred to as the auto-step, is presented in this paper and is used to estimate the parameters of the crack propagation model in real-time. The prognosis structure is first compares values of both the predicted and the measured defect sizes, and then, tunes the parameters of the crack propagation model. Simulation results obtained by the auto-step method are then compared with results obtained by the Recursive Least Square (RLS) adaptive filter. The proposed prognosis strategy is distinct itself from other approaches in terms of obtaining higher accuracy as well as faster convergence rate.

Topics: Roller bearings
Commentary by Dr. Valentin Fuster
2014;():V001T08A002. doi:10.1115/DSCC2014-6037.

This paper presents an approach to use Computational Fluid Dynamics (CFD) analysis for the development of a health monitoring system based on Symbolic Dynamic Filtering (SDF) for rotating machinery. A simplified model of a turbomachinery (single rotor) is analyzed using commercial CFD software with and without blade damages. Virtual pressure sensors are placed on the case of the turbomachinery directly above the rotating blades to measure the dynamic pressure pulse generated by the rotating blades. The pressure pulse profiles from the rotating rotor blades with and without blade damages are processed using SDF to determine the presence and magnitude of the fault. Various degrees of damage and effect of measurement noise are examined.

Commentary by Dr. Valentin Fuster
2014;():V001T08A003. doi:10.1115/DSCC2014-6119.

The rotor may operate at various working conditions in practice and the crack breathing behavior at different rotating speeds is essential for damage detection and health monitoring of rotor system. In this paper, the coupling of lateral and longitudinal vibration is investigated by building a Jeffcott rotor model with imbalance. By using D’Alambert Principle, four degree-of-freedom equation of motion is derived in fixed coordinate system and the crack model is built based on the fracture mechanics. Zero SIF method is used to determine the crack open area by computing the SIF of opening mode for every point in crack area. The stiffness matrix is updated every time step by integrating compliant coefficients over instantly calculated crack open area. In addition, the breathing behavior of the crack under axial excitation is studied in terms of several eccentricity phases and rotation speeds, which provide effective guidance for damage detection in such scenarios. The paper also explores the coupling effect of external axial loading on the vibration response and its effectiveness for damage detection.

Commentary by Dr. Valentin Fuster
2014;():V001T08A004. doi:10.1115/DSCC2014-6183.

A new guided wave imaging application for fast, low-cost ultrasound-based cargo scanning system is presented. The goal is the detection of high-atomic-number, shielding containers used to diminish the radiological signature of nuclear threats. This ultrasonic technology complements currently deployed X-ray-based radiographic systems, thus enhancing the probability of detecting nuclear threats.

An array of acoustic transceivers can be attached to the metallic structure of the truck to create a guided acoustic wave. Guided medium thickness and composition variation creates reflections whose placement can be revealed by means of an imaging algorithm. The knowledge of the reflection position provides information about the shielding container location inside the truck.

Reflected waves in the guided domain bounds may limit the performance of imaging methods for guided media. This contribution proposes a solution based on Fourier domain analysis, where plane wave components can be filtered out, thus removing non-desired contributions from bounds. Apart from this, the imaging algorithm can be used to recover information about material composition. Simulation-based examples are used for algorithm validation.

Topics: Containers , Imaging
Commentary by Dr. Valentin Fuster
2014;():V001T08A005. doi:10.1115/DSCC2014-6369.

Ensuring the reliability and availability of complex systems such as safe mechatronic systems or cost-sensitive machine components is of increasing importance. Besides the availability of problem-specific sensors and filtering techniques three major issues are of interest:

i) Preparation of the measured data (filtering),

ii) Interpretation of the data with respect to the machines state as well as to the machines’ remaining lifetime or guaranteed functionality, and

iii) establishing the required knowledge behind from available measurements and data.

Core of this contribution is the development and application of easy to apply and easy to interpret algorithms to be used directly with industrial data or measurements from technical systems in operation.

The three approaches applied are

AI: Acoustic Emission (AE) characterized by measurements in combination using a suitable filter to be designed,

AII: data analysis using operating system data feature capturing technique, and

AIII: Adaptive fuzzy-based filtering [1] with training and classification modules.

The approaches are developed in detail due to former research work [2], here they are applied and compared using the same experiment, the shown results are based on experiments. The three approaches use different algorithms but partially different signal sources (from the same experiment). Each of the approaches allows a different and distinguished problem-oriented insight to the complex wear process of the considered system, typical for mechanical engineering-related machines. The comparison between three different approaches for wear diagnosis can be considered as the main idea of this paper which allows insights into the advantages and disadvantages of each of these approaches.

Topics: Wear , Signals
Commentary by Dr. Valentin Fuster
2014;():V001T08A006. doi:10.1115/DSCC2014-6370.

In this contribution a recently developed new modeling and classification approach to be used with streamed measurement data of industrial processes is applied.

This briefly repeated approach can be used for fault classification and diagnostic purposes. The approach is based on a fuzzy-like modeling using statistical features from training data. Based on the trained model classification can be realized allowing to distinguish unknown data sets to the given number of data classes each related to states.

Beside the brief introduction to the proposed approach, experimental data are used to demonstrate the approach and the complex example distinguishing different wear states of machine components during operation.

Commentary by Dr. Valentin Fuster

Control Design for Drilling Automation

2014;():V001T09A001. doi:10.1115/DSCC2014-5926.

This paper presents the design and simulation of an indirect adaptive robust controller (IARC) for the rotatory drilling motion used in oil and gas exploration operations. To eliminate drill string vibrations, such as stick-slip, and achieve better control of drill bit rotating motion, an IARC controller was designed to compensate nonlinear friction torque directly and address system uncertainties during drilling. Simulation results are presented to illustrate the effectiveness of the designed IARC controller.

Commentary by Dr. Valentin Fuster
2014;():V001T09A002. doi:10.1115/DSCC2014-6081.

Developed in this paper is a new approach to subsea production two-phase flow modeling and control of pipeline and manifold assemblies. For that purpose, a reduced-order model is developed for transient two-phase gas-liquid flow in pipelines. First, a mechanistic model is used to calculate the steady-state pressure drop and liquid holdup. From this model, effective fluid properties are calculated and used as arguments to the dissipative distributed parameter model. A modal approximation technique is then used to render the model into a rational polynomial form appropriate for time-domain analysis and controller design. A new low-frequency magnitude correction is applied to the approximated transfer functions providing an improved matching for the steady-state gain without affecting the dynamics of the system. The resulting low-dimensional two-phase flow model is then used to coordinate the arriving pressures at the manifold for different GVF levels through electro-hydraulic valves located at the wellheads.

Commentary by Dr. Valentin Fuster
2014;():V001T09A003. doi:10.1115/DSCC2014-6109.

Managed Pressure Drilling (MPD) is an advanced pressure-control method that is used to precisely control the annular pressure throughout the wellbore in an oil well drilling. Because downhole measurements are unreliable due to slow sampling, transmission delay, and loss of communication for low or no-flow conditions, the challenge is to accurately estimate the flow and pressure along the annulus and the unknown in/out flux at the bottom of the well using only topside measurements. This paper describes the development of an adaptive control and observer for such problems that models the transport phenomenon as a 2×2 linear hyperbolic system. The adaptive design, which relies only on the measurements taken at the right boundary, is based on the backstepping method. The design is tested using data from a field scale flow-loop test conducted in Stavanger, Norway by the Statoil oil company. The results show that the observer converges to the actual value and that the update law accurately estimates the unknown parameter.

Topics: Pressure , Drilling
Commentary by Dr. Valentin Fuster
2014;():V001T09A004. doi:10.1115/DSCC2014-6164.

This paper investigates control of stick-slip oscillations in drilling from a linear matrix inequality perspective. Stick-slip oscillations include a period of no angular motion at the bit caused by a large static friction torque followed by a period of rapid angular motion at the bit caused by a build up of torque in the drilling pipe. Many of the model parameters are uncertain but belong to convex sets, and the friction torques are not easily modeled. The linear matrix inequality approach facilitates design of state feedback controllers in the presence of polytopic uncertainties and can be optimized to reject disturbance effects relative to outputs. Results indicate that the linear matrix inequality approach leads to a simple controller, successfully alleviates the stick-slip problem, and is robust to uncertainties.

Commentary by Dr. Valentin Fuster

Control of Ground Vehicles

2014;():V001T10A001. doi:10.1115/DSCC2014-6035.

This paper presents the sensitivity analyses on vehicle motions with regard to faults of in-wheel motors and steering motor for an electric ground vehicle (EGV) with independently actuated in-wheel rear motors. Based on the vehicle model, direct method is applied to determine, to what extent, that different actuator faults affect vehicle motions such as the longitudinal velocity, lateral velocity, and yaw rate. For motion indices like vehicle sideslip angle and longitudinal acceleration, linearizations around equilibrium points are conducted and their sensitivities to actuator faults are analyzed. Results show that all mentioned vehicle motions are more sensitive to the fault of steering motor than that of in-wheel motors. In addition, the effects on vehicle motions due to four types of faults, i.e. additive, loss-of-effectiveness, time-varying-gain and stuck-at-fixed-level faults, are examined through CarSim® simulations and vehicle experiments under a representative maneuver.

Commentary by Dr. Valentin Fuster
2014;():V001T10A002. doi:10.1115/DSCC2014-6080.

Typical drivers are not ready to react to unexpected collisions from other vehicles. The initial impact can startle the driver who then fails to maintain control. Since a loss of control leads to intense skidding and undesirable lateral motions, more severe subsequent events are likely to occur. To reduce the severity of possible subsequent (secondary) crashes, this paper considers both vehicle heading angle and lateral deviation from the original driving path. The research concept here is different from today’s electronic stability control systems in that it activates the differential braking even when the magnitude of yaw rate or vehicle slip angle is very high. In addition, the lateral displacement and yaw angle with respect to the road are part of the control objective. The Linear Time Varying Model Predictive Control (LTV-MPC) method is used, with the key tire nonlinearities captured through linearization. We consider tire force constraints based on the combined-slip tire model and their dependence on vehicle motion. The computed high-level (virtual) control signals are realized through a control allocation problem which maps vehicle motion commands to tire braking forces considering constraints. Numerical simulation and analysis results are presented to demonstrate the effectiveness of the control algorithm.

Commentary by Dr. Valentin Fuster
2014;():V001T10A003. doi:10.1115/DSCC2014-6092.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is currently being developed to predict and maintain vehicle handling capabilities through upcoming maneuvers. This system depends heavily on an understanding of the interplay between the vehicle’s longitudinal, lateral, and vertical forces, as well as their resulting moments. These vehicle dynamics impact the Performance Margin metric and ultimately the point at which the Intervention Strategy will modulate the throttle and brake controls. Real-time implementation requires the development of computationally efficient predictive models of the vehicle dynamics. A method for predicting future vehicle states for smooth but tortuous roads is developed in this work using perturbation theory. An analytical relationship between the change in these forces and the resulting change in the Performance Margin is also derived. This model is implemented in the predictor-corrector algorithm of the Intervention Strategy. Corrections to the predicted states are made at each time step using a detailed, full, non-linear vehicle model; this full vehicle model is a precursor to incorporation of the LAAVDS in a real vehicle. Eventually, this work will be expanded to include the impact of rough terrain.

Commentary by Dr. Valentin Fuster
2014;():V001T10A004. doi:10.1115/DSCC2014-6098.

Model predictive control (MPC) is a popular technique for the development of active safety systems. However, its high computational cost prevents it from being implemented on lower-cost hardware. This paper presents a computationally efficient predictive controller for lane keeping assistance systems. The controller shares control with the driver, and applies a correction steering when there is a potential lane departure. Using the explicit feedback MPC, a multi-parametric nonlinear programming problem with a human-in-the-loop model and safety constraints is formulated. The cost function is chosen as the difference between the linear state feedback function to be determined and the resultant optimal control sequence of the MPC problem solved off-line given the current state. The piecewise linear feedback function is obtained by solving the parametric programming with an approximation approach. The effectiveness of the controller is evaluated through numerical simulations.

Commentary by Dr. Valentin Fuster
2014;():V001T10A005. doi:10.1115/DSCC2014-6144.

Driven by the emergence of autonomous/semi-autonomous driving technologies, the mixed situation of autonomous vehicles and human drivers is of considerable significance. Toward this end, it is necessary to better understand human driving characteristics so as to predict the actions of the other cars. In this regard, we develop a basic framework for modeling driver behaviors in view of human prediction ability. Through the game theoretic estimation of the counterpart’s behaviors and the corresponding time-evolution of unsafe collision areas, we compute an objective collision model. In turn, we design a human-like predictive perception model on collision with an adjacent vehicle based on the objective collision model and the driver’s subjective level of safety assurance. Since drivers have different safety requirements, the subjective estimate on the collision was designed as a region in which has less safety than the driver’s own safety requirement in the objective probabilistic collision prediction. The region that is subjectively perceived based on the driver’s own safety standard is regarded as a deterministic unsafe region for the driver. That is to say, the subjective perception acts as a collision area with the collision probability of 1 so that the driver should avoid while driving. In our subsequent work, we will address the issue of controller design to avoid the subjective collision estimation.

Commentary by Dr. Valentin Fuster
2014;():V001T10A006. doi:10.1115/DSCC2014-6358.

In this paper, we investigate the nonlinear dynamics of connected vehicle systems. Vehicle-to-vehicle (V2V) communication is exploited when controlling the longitudinal motion of a few vehicles in the traffic flow. In order to achieve the desired system-level behavior, the plant stability and the head-to-tail string stability are characterized at the nonlinear level using Lyapunov functions. A motif-based approach is utilized that allows modular design for large-scale vehicle networks. Stability analysis of motifs are summarized using stability diagrams, which are validated by numerical simulations.

Topics: Stability , Vehicles
Commentary by Dr. Valentin Fuster

Control of Manipulators

2014;():V001T11A001. doi:10.1115/DSCC2014-6033.

This paper presents an extensive experimental study of the first steps of the Hume robot. Hume is an adult sized, 20 kg, series-elastic, point-foot biped robot capable of very fast leg movements. In this study, Hume is constrained to planar motion by a linkage mechanism. We present our application of phase space planning to one, two, and three step walking, the last one over an obstacle. In the implementation, we modified the original theory and added ad-hoc adjustments since the robot could not follow the original theory’s planned walking trajectories despite their theoretical stability. We present a good correlation between the phase space plans and our various experiments, and an analysis of the robot’s final behavior. Overall the planner and ad-hoc modifications allowed us to execute very smooth gaits even over non-flat surfaces but at the same time demonstrated the shortcomings of open loop techniques.

Commentary by Dr. Valentin Fuster
2014;():V001T11A002. doi:10.1115/DSCC2014-6189.

In this paper, we present a robotic locomotor with inertia-based actuation. The goal of this system is to generate various gait modes of a baton, consisting of two masses connected with a massless rod. First, a model for a baton prototype called Pony II is presented. This model incorporates the double-action inertial actuation generated by two rotating pendulums, spinning at constant angular velocities in opposite directions. This system allows regulation of the inertial forces generated by the spinning masses. In addition, it provides control over the orientation of the resultant inertial force. Numerical simulations of four stable gaits are presented: dragging, tapping, galloping, and hopping. We also developed an experimental prototype, called Pony II, consisting of the double-action actuators. The robot successfully generates all the simulated gaits. In addition, we show that the robot is capable of generating progression on low friction surfaces.

Topics: Robots , Pendulums
Commentary by Dr. Valentin Fuster
2014;():V001T11A003. doi:10.1115/DSCC2014-6207.

This paper studies the effects of damping and stiffness feedback loop latencies on closed-loop system stability and performance. Phase margin stability analysis, step response performance and tracking accuracy are respectively simulated for a rigid actuator with impedance control. Both system stability and tracking performance are more sensitive to damping feedback than stiffness feedback latencies. Several comparative tests are simulated and experimentally implemented on a real-world actuator to verify our conclusion. This discrepancy in sensitivity motivates the necessity of implementing embedded damping, in which damping feedback is implemented locally at the low level joint controller. A direct benefit of this distributed impedance control strategy is the enhancement of closed-loop system stability. Using this strategy, feedback effort and thus closed-loop actuator impedance may be increased beyond the levels possible for a monolithic impedance controller. High impedance is desirable to minimize tracking error in the presence of disturbances. Specially, trajectory tracking accuracy is tested by a fast swing and a slow stance motion of a knee joint emulating NASA-JSC’s Valkyrie legged robot. When damping latencies are lowered beyond stiffness latencies, gravitational disturbance is rejected, thus demonstrating the accurate tracking performance enabled by a distributed impedance controller.

Commentary by Dr. Valentin Fuster
2014;():V001T11A004. doi:10.1115/DSCC2014-6212.

The “self-recovery” phenomenon is a seemingly curious property of certain underactuated dissipative systems in which dissipative forces always push the system to a pre-determined equilibrium state dependent on the initial conditions. The systems for which this has been studied are Abelian, with all system velocity interactions due entirely to inertial effects. In this paper we also consider Abelian systems, but in the context of principal bundles, and introduce drag in addition to inertial interactions, allowing us to show that the same conservation that induces self-recovery now depends on the trajectories of the system inputs in addition to initial conditions. We conclude by demonstrating an example illustrating the conditions derived from our proof, along with an observation that the present analysis is insufficient for self-recovery in non-Abelian systems.

Commentary by Dr. Valentin Fuster
2014;():V001T11A005. doi:10.1115/DSCC2014-6330.

The development of control strategies that allow stiff industrial robots to operate safely in unstructured environments is a significant challenge. This paper integrates two strategies that improve safety for industrial manipulators in uncertain conditions. First, software compliance in the task space is implemented using force feedback. End-effector compliance is vital for many tasks, such as interacting with humans or manipulating uncertain payloads. Beyond compliance, a collision detection algorithm detects collisions based on joint torque deviation from a dynamic model. Collisions can be detected at any point along the manipulator via loading or impulse anomalies. Joint torque data is typically noisy, and the accuracy of the robot dynamic model is limited, so an Extended Kalman Filter (EKF) was developed to improve the torque estimates. Experiments and demonstrations were performed using a commercially available 7DOF industrial robot. The EKF improved collision detection during unplanned contact tasks, and the method described here is hardware agnostic and extensible.

Commentary by Dr. Valentin Fuster

Control of Mechatronic Systems

2014;():V001T12A001. doi:10.1115/DSCC2014-6104.

The magnetorheological (MR) control valve is a major component in MR fluid systems to achieve controllable pressure drop or damping characteristics in practice. However, the optimal design of MR control valve is fairly complex due to large extent of design parameters from both magnetic flux generation and mechanical flow characteristics, as well as different requirements or constraints in practical applications. In this paper, the analytical electro-mechanic-magnetic coupling model of the MR control valve with annular-radial flow path is firstly investigated to quantitatively predict the relationship between design parameters and achievable performances such as pressure drop and dynamic range etc.. And then comparison results based on analytical analysis and finite element method are presented to validate the effect model utilized in MR valves. Consequently, a performance-oriented optimization of MR control valves with annular-radial flow path in a non-dimensional design concept is developed through minimizing reciprocal of dynamic range and identifying several optimal internal design parameters subject to predefined constraints under fairly less quantity of combined external design parameters.Finally, the inherent sensitivity of achievable performances with respect to external design parameters is analyzed to provide practical instructions for appropriate specification of the MR control valve.

Topics: Optimization , Valves
Commentary by Dr. Valentin Fuster
2014;():V001T12A002. doi:10.1115/DSCC2014-6234.

An adaptive multi-loop mode (AMLM) imaging of atomic force microscope (AFM) is proposed. Due to its superior image quality and less sample disturbances, tapping mode (TM) imaging is currently the de facto most widely used imaging technique. However, the speed of TM-imaging is substantially limited, and becoming the major bottleneck of this technique. The proposed AMLM-imaging overcomes the limits of TM-imaging by utilizing control techniques to substantially increase the speed of TM-imaging while preserving the advantages of TM-imaging. The AMLM-imaging is tested and demonstrated through imaging a PtBA sample in experiments, and the experiment results demonstrated that the image quality over large-size imaging (50 μm by 25 μm) achieved at the scan rate of 25 Hz is at the same level of that when using TM-imaging at 1 Hz, while the probe-sample interaction force is smaller than that of the TM-imaging at 2.5 Hz.

Commentary by Dr. Valentin Fuster
2014;():V001T12A003. doi:10.1115/DSCC2014-6257.

Active magnetic bearings (AMBs) provide support to rotating machinery through magnetic forces which are regulated through active feedback control. As AMBs continue to establish themselves as a proven technology, many classical and modern techniques are being employed to address the design of the control law. The current work studies three of the controller design techniques which are common in the literature for AMB applications: PID, LQG, and μ-synthesis. A controller is designed for an AMB system using each of the three techniques. Details of the design processes are given and the resulting controllers are compared. Finally, the controllers are implemented on the experimental system and the closed-loop characteristics are measured and evaluated. This work provides a common case study to demonstrate the strengths and weaknesses of PID, LQG, and μ-synthesis control methodologies as applied to a specific AMB system.

Commentary by Dr. Valentin Fuster
2014;():V001T12A004. doi:10.1115/DSCC2014-6289.

Inkjet printing technologies have been common and well developed over the past few decades, and more recently have gained significant acceptance in functional printing and additive manufacturing applications. Control of dot gain in the deposition process is a desirable capability for a printing system from the perspective of process control and throughput, and preliminary data suggests dot gain and drop volume can be controlled in inkjet systems through manipulation of the reservoir back pressure. In order to help facilitate further exploration, the design of a back pressure control system is proposed, and the system modeled, with linear and nonlinear control designs proposed and compared in simulation for this nonlinear plant application, where the nonlinear control design, a sliding mode controller, outperforms the tested linear control design.

Commentary by Dr. Valentin Fuster
2014;():V001T12A005. doi:10.1115/DSCC2014-6307.

Atomic force microscopes use a probe to interface with matter at the nanoscale through a variety of imaging or manipulation methods. A dual-probe atomic force microscope (DP-AFM) has been proposed for simultaneous imaging and manipulation. One challenge of DP-AFM is probe-to-probe contact, which may occur intentionally such as when locating one probe with the other. This work studies the stability for such interactions where the 1st probe is in the tapping mode (typically used for imaging) and 2nd probe is in the contact mode (typically used for manipulation). A state dependent switched model is proposed for DP-AFM. A theorem is proposed for uniformly ultimately bounded (UUB) stability of switched systems under a sequence nonincreasing condition and applied to the DP-AFM problem.

Commentary by Dr. Valentin Fuster

Controls for Manufacturing

2014;():V001T13A001. doi:10.1115/DSCC2014-5949.

Electrospinning produces submicron fibers for a variety of applications using a wide range of polymers. Achieving the desired fiber diameter, maximizing productivity, and minimizing variation are important production objectives. This paper addresses several important areas needed to develop a general electrospinning control approach including: developing a correlation between measurements, process conditions, and the resulting fiber diameter, developing a method to determine an operating regime that meets manufacturing objectives, and identifying process dynamics for controller design.

Commentary by Dr. Valentin Fuster
2014;():V001T13A002. doi:10.1115/DSCC2014-5960.

Feedforward control can significantly improve the performance of industrial motion systems through compensation of the servo error induced by the reference signal. Recently, new feedforward tuning algorithms have been proposed that exploit measured data from previous tasks and a suitable feedforward parametrization to attain high servo performance. The aim of this paper is to formulate a design procedure for motion feedforward tuning. Experimental results on an industrial motion system illustrate the improvement in servo performance obtained by means of the proposed tuning procedure.

Commentary by Dr. Valentin Fuster
2014;():V001T13A003. doi:10.1115/DSCC2014-6143.

When traversing sharp corners, manufacturing machines are forced to tradeoff speed and accuracy. The most common way of reducing this tradeoff is to smooth the sharp corner using a pre-specified curve (e.g., a circular arc or spline). However, pre-specified curves cannot guarantee optimal performance. This paper presents a preliminary investigation into the potential of using methods from optimal control to minimize this tradeoff. First, a useful simplification is made to the exact cornering problem to make it tractable. Dynamic programming is then used to determine the best free-form curve that minimizes corner traversal time while adhering to path tolerance and machine kinematic constraints. Significant improvements in cornering time are demonstrated compared to two methods that use pre-specified curves. However, dynamic programming is found to be too computationally costly, thus impractical. Less computationally intensive techniques in optimal control are considered for future work.

Commentary by Dr. Valentin Fuster
2014;():V001T13A004. doi:10.1115/DSCC2014-6300.

In this paper, new design of micro-gripper with shape memory alloy (SMA) actuator is presented. Double SMA actuators were used to enhance the performance of the micro-gripper by using hinge mechanisms; the little displacement of the SMA wire is converted into larger displacement of the tips of the micro-gripper. Stainless steel (St 304) was used as a main material of the gripper structure. Shape memory alloy (Ni-Ti) wires were used as actuators. Finite element model analysis (FEA) using ANSYS software package was used to simulate displacement and stress analysis on the micro gripper. Finally a comparison between the enhanced design and the initial one showed better results in terms of increasing the gripper stroke and reducing the stress on the gripper joints.

Commentary by Dr. Valentin Fuster
2014;():V001T13A005. doi:10.1115/DSCC2014-6318.

In this paper, the process control of a magnetostrictive-actuator-based dual-stage microforming system is studied. Microforming has recently become an emerging advanced manufacturing technique for fabricating miniaturized products. Particularly, miniaturized desktop microforming system based on unconventional actuators possesses great potential in attaining both high productivity and low cost. Process control of such miniaturized microforming systems, however, is challenging and still at its early stage. The challenge arises from the complicated behaviors of the actuators used, the switching and transition of the actuation/motion, and the uncertainty of the system dynamics during the entire microforming process. During the microforming process, the dynamics and the hysteresis effects of magnetostrictive actuator can be excited, resulting in positioning errors of the workpieces in both trajectory tracking and output transition. Rapid transition between tracking and transition is also accompanied with substantial variation of the system dynamics. Additional challenges exist due to the use of multi-stage actuators and the augmentation of ultrasonic vibrations to the microforming process. In this paper, a control framework integrating iterative learning control and optimal transition trajectory design along with feedforward-feedback control is proposed to achieve high speed and high quality in microforming. The efficacy of the proposed control strategies is demonstrated through experimental implementation.

Commentary by Dr. Valentin Fuster
2014;():V001T13A006. doi:10.1115/DSCC2014-6322.

In this paper we employ a modified filtered-x least mean squares (MFX-LMS) method to synthesis an adaptive repetitive controller for rejecting periodic disturbances at selective frequencies. We show how a MFX-LMS algorithm can be utilized when the reference signal is deterministic and periodic. A new adaptive step size is proposed with the motivation to improve the convergence rate of the MFX-LMS algorithm and fade the steady state excess error caused by the variation of estimated parameters in a stochastic environment. A novel secondary path modeling scheme is proposed to compensate for the modeling mismatches online. We further discuss the application of this adaptive controller in hard disk drives that use Bit Patterned Media Recording. Finally we present the results of comprehensive realistic numerical simulations and experimental implementations of the algorithms on a hard disk drive servo mechanism that is subjected to periodic disturbances known as repeatable runout.

Topics: Algorithms
Commentary by Dr. Valentin Fuster

Distributed Control

2014;():V001T14A001. doi:10.1115/DSCC2014-5878.

A cooperative control problem where N Unmanned Aerial Vehicles (UAVs) are assigned to eliminate M main targets is studied in this paper. The environment where these assignments are performed also includes T >> M threats that pose a risk to the group of UAVs. A decentralized optimization problem is presented where agents try to minimize a total cost that combines distance to reach main targets and exposure to threats. The main novelty here is the use of limited resources by the UAVs to eliminate threats while on their way to reach main targets. This option improves the trajectories of vehicles by further reducing total cost but it adds complexity to the optimization problem. The solution to this extended problem provides optimal decisions regarding the selection of threats to eliminate, and the corresponding trajectories to follow, in order to minimize total cost. Due to constraints imposed by communication topologies, agents implement a decentralized auction scheme in order to assign UAVs to threats while avoiding conflicts on those assignments. This paper describes the specific constraints concerning the decentralized decision process and its effects in recomputing new costs. The paper also offers preliminary results that provide coordinated selection of UAV paths and choice of threats to attack.

Commentary by Dr. Valentin Fuster
2014;():V001T14A002. doi:10.1115/DSCC2014-5879.

In many multi-agent scenarios, agents must balance both local and global performance and collaboration objectives with the constraints of efficient resource utilization. Here, consensus problems with fixed communication graphs are considered, where agents strive to reach a common decision value in minimum time while simultaneously minimizing a performance cost that measures the deviation of the decision value from the desired value. The paper offers preliminary results on the selection of meaningful decision values that approximate optimal solutions. The proposed approach shows a fast convergence time and also reduces the overall number of information transmissions by the agents in the network.

Topics: Collaboration
Commentary by Dr. Valentin Fuster
2014;():V001T14A003. doi:10.1115/DSCC2014-5893.

In this paper, we consider the problem of formation control of multi-agent systems where the desired formation is dynamic. This is motivated by applications, such as obstacle avoidance, where the formation size and/or geometric shape needs to vary in time. Using a single-integrator model and rigid graph theory, we propose a new control law that exponentially stabilizes the origin of the nonlinear, inter-agent distance error dynamics and ensures tracking of the desired formation. The extension to the formation maneuvering problem is also discussed. Simulation results for a five-agent formation demonstrate the control in action.

Commentary by Dr. Valentin Fuster
2014;():V001T14A004. doi:10.1115/DSCC2014-5950.

The spread of contaminant into the environment due to a high volume of leakage from point sources is a very real threat in the modern world. Since the contaminant can often be dangerous to human operators, multiple robotic agents equipped with suitable sensors are playing an increasingly important role in the so-called contaminant detection problem than before. This paper proposes a contaminant detection methodology which can not only locate the (possibly multiple) source of the contaminant, but also estimate the intensity in an environment evolving over both space and time. The methods can deal with measurement noise and do not need any gradient information.

Commentary by Dr. Valentin Fuster
2014;():V001T14A005. doi:10.1115/DSCC2014-6041.

A primary factor limiting the development, testing, and validation of decentralized algorithms for large-scale multi-robot teams is the high cost of the available systems. When a successful test necessitates that an algorithm functions on dozens or even hundreds of robots simultaneously, a low price tag on each robot is crucial. This paper presents Spider-Bots, a low cost platform for testing and validating control algorithms for multi-robot swarms. The platform is comprised of centimeter-scale mobile robots that can communicate wirelessly and interact with their environment, along with easy to use software libraries. The resulting platform was validated by testing its ability to execute and record data from three separate algorithms: Set-point navigation, object manipulation, and collision avoidance.

Commentary by Dr. Valentin Fuster
2014;():V001T14A006. doi:10.1115/DSCC2014-6106.

A class of cyber-physical systems that is gradually attracting increased scientific attention is Large-Scale Actuator Networks (LSAN). A prospective application of actuator networks is distributed manipulation. Distributed manipulation has the potential to become a game-changing technology in the area of industrial automation. To examine this class of systems, this paper presents a reactive elastic surface that autonomously morphs its shape by using a grid of linear actuators to transport an object into a target location. The combined action of the actuator grid overcomes the limitations of individual actuators, resulting in a system with multiple degrees-of-freedom. Experimental results illustrate the applicability of the platform.

Topics: Actuators
Commentary by Dr. Valentin Fuster

Dynamic Systems Modeling for the Design and Optimization of Vehicle Systems

2014;():V001T15A001. doi:10.1115/DSCC2014-5848.

Nowadays, power-split hybrid electric vehicles (PS-HEV) are very popular mainly thanks to the success of Toyota Prius. Despite their superior performance, the design and control of PS-HEVs are non-trivial due to the large number of design candidates and the complex control problems. For instance, there exist twelve ways to connect the four components (two motor/generators, an engine, and a driving wheel) with a single planetary gear-set (PG), and the number increases to 1152 possible configurations when using two PGs. Moreover, if we consider the final drive (FD) and PG ratios as design variables, finding the best design becomes intractable. In this study, we introduce a simple yet powerful way to find the optimal designs of single PG PS-HEVs. The suggested method consists of two parts — full-load analysis and light-load analysis. The full-load analysis computes 0–100kph times to evaluate acceleration performance of all designs using instantaneous optimization approach. The light-load analysis evaluates the fuel economy of selected designs (designs with acceptable acceleration performance) using equivalent consumption minimization strategy (ECMS). Note that the sun-to-ring (SR) gear ratio and the FD ratio are considered design variables, and thus one can see how fuel economy and acceleration performance of each configuration vary with SR and FD ratios. Based on these analyses, the optimal design that balances full-load and light-load performances can be selected.

Commentary by Dr. Valentin Fuster
2014;():V001T15A002. doi:10.1115/DSCC2014-6028.

Double Planetary Gear (PG) power-split hybrid powertrains have been used in production vehicles from Toyota and General Motors. Some of the designs use clutches to achieve multiple operating modes to improve powertrain operation flexibility and efficiency at the expense of higher complexity. In this paper, an automatic modeling and screening process is developed, which enables exhaustively search through all designs with different configurations, clutch locations and operating modes. A case study was conducted based on the configuration used in the model year 2010 Prius and Camry hybrids. It was found that by adding clutches, fuel economy can be improved significantly for plug-in hybrid (charge depletion) operations.

Topics: Gears , Modeling
Commentary by Dr. Valentin Fuster
2014;():V001T15A003. doi:10.1115/DSCC2014-6062.

This paper presents systematic analysis and design of power split hybrid configurations using a single planetary gearset and two electric machines for human-powered vehicles. In our design methodology, the cyclist is treated as an integrated part of the powertrain, and the cyclist’s power output is augmented by the battery power, instead of being completely replaced. To obtain the optimal design, all the 12 possible power split hybrid configurations are investigated, and several performance indices, including the cyclist’s oxygen consumption, stamina reduction, and pedaling speed preference, are considered in the optimization problem to evaluate the bicycle design. The dynamic programming technique is used to solve the optimization problem. The optimal design, HyBike-i2, has the pedal connected to the carrier gear and one electric machine to the ring gear on the planetary gearset. The other electric machine and the driven wheel are connected to the sun gear. This design outperforms the normal bicycle (no power assist) and two traditional electric bicycles, and achieves substantial reduction in both the cyclist’s stamina discharge and oxygen consumption when the vehicle operates in the charge-sustaining mode.

Topics: Vehicles
Commentary by Dr. Valentin Fuster
2014;():V001T15A004. doi:10.1115/DSCC2014-6065.

In the transportation industry, the need to improve powertrain efficiency and provide additional power to the many amenities has encouraged research on engine waste heat recovery. Approximately one-third of the gasoline or diesel fuel energy passes through the engine’s exhaust system as heat. With ongoing developments in thermoelectric materials and module design, thermoelectric power generation has a potential use in engine heat recovery. In this study, the capability of generating usable power by thermoelectric generation from the exhaust heat of a three-cylinder, 697 cubic centimeter diesel engine was investigated. From experimental testing, the maximum power output and maximum current for a single module and four modules connected in series was 0.49W with 0.437A, and 2.81W with 0.60A, respectively. To harvest larger power magnitude from the waste heat, the modules will be configured in a co-axial manner along the pipe. Other possible applications include stationary power generation systems in which added weight does not effect overall performance.

Commentary by Dr. Valentin Fuster
2014;():V001T15A005. doi:10.1115/DSCC2014-6123.

High resolution elevation mapping is useful for precise field operations. To achieve a good operation performance, the requirement of the field shape accuracy can be centimeter-level in some tasks. This paper presents a method of conducting high resolution elevation mapping with vehicle-borne sensors. To achieve this purpose, a laser range sensor obtains geometric information of the ground surface while an Inertial Navigation System (INS) and vision sensor provide high resolution measurements of the moving vehicle’s current location and attitude. The high frequency information from the INS captures the vehicle dynamics, and the low frequency vision sensor data enables vehicle self-localization by eliminating drift error in the INS measurements. A test run of this system was conducted experimentally. And the inclusion of vision-based measurements was shown to improve the accuracy of the ground elevation comparing with an INS-only method.

Commentary by Dr. Valentin Fuster
2014;():V001T15A006. doi:10.1115/DSCC2014-6290.

An approach to control a hydrostatic dynamometer for the Hardware-In-the-Loop (HIL) testing of hybrid vehicles has been developed and experimentally tested. The hydrostatic dynamometer used, which is capable of regeneration, was specifically designed and built in-house to evaluate the fuel economy and control strategy of a hydraulic hybrid vehicle. The control challenge comes from the inertia of the dynamometer being only 3% of that of the actual vehicle so that the dynamometer must apply, in addition to any drag torques, acceleration/deceleration torques related to the difference in inertias. To avoid estimating the acceleration which would be a non-causal operation, a virtual vehicle concept is introduced. The virtual vehicle model generates a reference speed profile which represents the behavior of the actual vehicle if driven on the road. The dynamometer control problem becomes one of enabling the actual vehicle-dyno shaft to track the speed of the virtual vehicle, instead of directly applying a desired torque. A feedback/feedforward controller was designed based upon an experimentally validated dynamic model of the dynamometer. The approach was successfully tested on a power-split hydraulic hybrid vehicle with acceptable speed and torque tracking performance.

Commentary by Dr. Valentin Fuster

Dynamics and Control of Mobile and Locomotion Robots

2014;():V001T17A001. doi:10.1115/DSCC2014-5868.

A novel nonlinear trajectory tracking controller for underactuated unmanned surface vessels is presented. A comprehensive planar model of the vessel with two control inputs is considered such that the system is represented by the equations of motion comprised of two double integrators subject to a second-order nonholonomic constraint. Given a target trajectory, a transitional desired trajectory is generated that uniformly satisfies the nonholonomic constraint and actuator saturation constraints. The system error dynamics is then modeled using the equations of motion and the transitional desired trajectory. A finite time sliding mode control law is developed to stabilize the yaw rotation which is robust to model uncertainties and disturbances. Consequently, the resulting reduced-order system is asymptotically stabilized via the surge force. Examples are presented and demonstrate that the approach provides trajectories and tracking control inputs which are suitable for real world applications.

Commentary by Dr. Valentin Fuster
2014;():V001T17A002. doi:10.1115/DSCC2014-6111.

Energy storage is a major limiting factor for small unmanned ground vehicle endurance. This paper presents a hybrid model of a robot power system and a method to optimize power production and limit power loss for extended UGV operation. The optimization is based on a hybrid automaton model of the power system and produces the optimal controls for the different power components. An abstraction of power use and averaging of dynamics within a state can model the system with sufficient accuracy for power system optimization. Simulation studies of a Packbot equipped with a fuel cell and a battery are presented. The optimized power system is shown to require less energy over the mission compared to a baseline controller.

Topics: Robots , Modeling
Commentary by Dr. Valentin Fuster
2014;():V001T17A003. doi:10.1115/DSCC2014-6125.

Buildings represent a large portion, approximately 40%, of all US energy use and carbon emissions. Significant savings can be found by conducting energy audits of the buildings, but the extensive training and cost of the audits prevent more widespread use. Automating the audit process with robots can greatly reduce the cost and provide more information to give better recommendations. This paper is the first in a series that proposes a system of autonomous robots that can conduct energy audits.

Specifically, this paper presents an overview of the autonomous system and details an unmanned aerial vehicle (UAV) platform which is used to perform automated lighting audits. Also, modifications to an existing exploration algorithm are proposed that will allow autonomous exploration of an unknown, GPS-denied environment while identifying and navigating to targets in real-time. This new algorithm is called SRT-Target. The UAV navigates to the lights, the target objects, in order to take additional measurements so that the light type can be determined. Movement of the UAV can be limited by a calibration factor β to account for sensor capabilities of the target sensor. Simulations of the algorithm show the exploration of the unknown area and the UAV moving to targets as they are identified.

Commentary by Dr. Valentin Fuster
2014;():V001T17A004. doi:10.1115/DSCC2014-6126.

Buildings are responsible for approximately 40% of all US energy use and carbon emissions. There exists large potential to improve building efficiency through retro-commissioning, but expense and required expertise of building auditors limit current implementation. Autonomous robotic assessments have the potential to provide consistent building energy audits with reduced cost and enhanced capabilities. As a first step in automating building audits, this paper presents work on automating the lighting analysis of a building.

As an aerial vehicle navigates and explores a room, the prototype system captures images and collects spectrometer readings. These data are used to quantify and classify lighting in a room. Additionally, images acquired from the optical camera are merged to form a composite image of the area. This composite image is used for navigation to lights to record spectrometer readings. Lighting type is then classified from these spectrometer readings. The combined lighting quantification and classification is used to create a topology map of light levels. The combined data are used to perform a thorough analysis of lighting and make lighting recommendations.

Commentary by Dr. Valentin Fuster
2014;():V001T17A005. doi:10.1115/DSCC2014-6190.

This paper presents a robust control design for a low-cost mobile robot under modeling uncertainties and external disturbances. We use a radial basis function neural network (RBFNN) to estimate and compensate for the model uncertainties and external disturbances. The proposed control design is model-free with guaranteed stability and good path-following performance. The RBFNN weight regulation and adaptive gains are designed based on the Lypanov method. Simulation and experimental results illustrate the design and demonstrate the strength of the proposed control applied to a nonholonomic wheeled mobile robot driven by low-cost permanent magnet dc motors without shaft encoders. The comparison results between proposed control and feedback linearization control confirm the effective role of the compensator in terms of precision, simplicity of design and computations.

Commentary by Dr. Valentin Fuster
2014;():V001T17A006. doi:10.1115/DSCC2014-6328.

Surgical resection of deep intracranial tumors under image guidance has significant challenges. The surgeon cannot see beyond the line of sight and it is also difficult to avoid the functional nerves along the path. In this context, the design of a Minimally Invasive Neurosurgical Intracranial Robot (MINIR-II) under continuous MRI is critical. The primary goal of the overall procedure is to avoid critical brain structures to reach the tumor location. Upon reaching the tumor location, the electro-cautery at the robot tip should be controlled to resect the tumor. The new MINIR-II proposed in this work, though not yet MRI compatible, is a dexterous serial chain tendon-driven robot with larger inner space, smaller outer diameter, and less coupling effect of the tendons during actuation. Each joint of the robot was attached with two tendons and they were routed outside the robot around a pulley to achieve rotational degree of freedom. The four-joint assembled robot was manufactured using a rapid prototyping machine and was tested by an experimental setup to demonstrate the motion of the robot.

Commentary by Dr. Valentin Fuster

Electrochemical Energy Systems

2014;():V001T19A001. doi:10.1115/DSCC2014-6158.

This paper proposes a model-based approach for the fuel cell flooding diagnostics problem. The cathode channel flooding and the GDL flooding diagnostic problems are decoupled and formulated as standard joint state and parameter estimation problems, with the amounts of the liquid water treated as varying system parameters to be identified. The unscented Kalman Filter technique has been applied to solve these problems. Simulation results prove the applicability of the cascading unscented Kalman filter design for flooding diagnostics.

Commentary by Dr. Valentin Fuster
2014;():V001T19A002. doi:10.1115/DSCC2014-6254.

This paper introduces a method to estimate battery state of health (SoH) via health-relevant electrochemical features. Battery state of health estimation is a critical part of battery management because it allows for balancing the trade-off between maximizing performance and minimizing degradation. In this paper, a health-relevant electrochemical feature, the side reaction current density, is used as the indicator of battery SoH. An estimation algorithm is required due to the unavailability of the side reaction current density via noninvasive methods. In this paper, Retrospective-Cost Subsystem Identification (RCSI) is used to estimate the side reaction current density via identification of an unknown battery health subsystem that generates the side reaction current density. Simulation results are provided for constant current charge and discharge cycles with different C rates. A current profile for an electric vehicle (EV) going through Urban Dynamometer Driving Schedule (UDDS) cycles is also used as the excitation signal during estimation. The simulations show promising results in battery health dynamic identification and side reaction current density estimation with RCSI.

Commentary by Dr. Valentin Fuster
2014;():V001T19A003. doi:10.1115/DSCC2014-6270.

This paper uses the principles of electrochemistry to derive a simple second-order model of lithium-ion battery dynamics. Low-order lithium-ion battery models exist in the literature, but are typically either linear, empirical, or both. Our goal, in contrast, is to obtain a model simple enough for control design but grounded in the principles of electrochemistry. The model reduction approach used in this paper has the added advantage of leading to a novel analytic expression for the capacitance associated with voltage relaxation. A process for identifying model parameters from experiments is outlined, and experimental results are used to evaluate the validity of the model.

Commentary by Dr. Valentin Fuster
2014;():V001T19A004. doi:10.1115/DSCC2014-6272.

This paper shapes the periodic cycling of a lithium-ion battery to maximize the battery’s parameter identifiability. The paper is motivated by the need for faster and more accurate lithium-ion battery diagnostics, especially for transportation. Poor battery parameter identifiability makes diagnostics challenging. The existing literature addresses this challenge by using Fisher information to quantify battery parameter identifiability, and showing that test trajectory optimization can improve identifiability. One limitation is this literature’s focus on offline estimation of battery model parameters from multi-cell laboratory cycling tests. This paper is motivated, in contrast, by online health estimation for a target battery or cell. The paper examines this “targeted estimation” problem for both linear and nonlinear second-order equivalent-circuit battery models. The simplicity of these models leads to analytic optimal solutions in the linear case, providing insights to guide the setup of the optimization problem for the nonlinear case. Parameter estimation accuracy improves significantly as a result of this optimization. The paper demonstrates this improvement for multiple electrified vehicle configurations.

Topics: Circuits , Batteries
Commentary by Dr. Valentin Fuster
2014;():V001T19A005. doi:10.1115/DSCC2014-6274.

This paper presents a new method for estimating the capacity of a lithium ion battery cell in the presence of a reference cell — the parameters of which are well characterized — in series with it. The method assumes that both cells are cycled using the same current trajectory starting from the same state of charge (e.g. fully charged). Voltage measurements for both cells as well as current measurements for the series string constitute the input to a nonlinear least squares minimization problem. The goal of this problem is to estimate the capacity of the cell given the difference between its voltage and that of the reference cell. We refer to this as the differential estimation problem, and use Monte Carlo simulation to compare it to the more traditional approach of estimating the capacity of each cell in a battery string independently using its current/voltage measurements. Two key conclusions emerge from this simulation. Compared to traditional estimation, differential estimation results in capacity estimates whose variance is (i) twice as sensitive to voltage measurement noise but (ii) significantly less sensitive to current measurement noise. This makes differential estimation more appealing for battery packs with high current measurement noise and low voltage measurement noise.

Commentary by Dr. Valentin Fuster
2014;():V001T19A006. doi:10.1115/DSCC2014-6352.

In electric vehicle applications, batteries are usually packed in modules to satisfy the energy and power demand. To facilitate the thermal management of a battery pack, a model-based observer could be designed to estimate the temperature distribution across the pack. Nevertheless, cost target in industry practice drives the number of temperature sensors in a pack to a number that is not sufficient to yield observability of all the temperature states. This paper focuses on formulating the observer design and sensor deployment strategy that could achieve the optimal observer performance under the frugal sensor allocation. The considered observer performance is the estimation errors induced by model and sensor uncertainty. The observer aims at minimizing the worst-case estimation errors under bounded model and sensor uncertainty.

Commentary by Dr. Valentin Fuster

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