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Model Predictive Sliding Mode Control: For Constraint Satisfaction and Robustness

[+] Author Affiliations
Yizhou Wang, Wenjie Chen, Masayoshi Tomizuka

University of California at Berkeley, Berkeley, CA

Badr N. Alsuwaidan

King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia

Paper No. DSCC2013-4067, pp. V003T44A005; 10 pages
doi:10.1115/DSCC2013-4067
From:
  • ASME 2013 Dynamic Systems and Control Conference
  • Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control
  • Palo Alto, California, USA, October 21–23, 2013
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5614-7
  • Copyright © 2013 by ASME

abstract

A novel combination of model predictive control (MPC) and sliding mode control (SMC) is presented in this paper. The motivation is to inherit the ability to explicitly deal with state and input constraints from MPC, and the good robustness property from SMC. The design of the finite-time optimal control problem and the conditions for the persistent feasibility and the closed-loop stability are discussed. Simulation results are shown to demonstrate the nominal and robust performance of the proposed control algorithm.

Copyright © 2013 by ASME

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