Wang, Yizhou (University of California at Berkeley), Chen, Wenjie (University of California at Berkeley), Tomizuka, Masayoshi (Univ of California, Berkeley), Alsuwaidan, Badr (King Abdulaziz City for Science and Technology)

Model Predictive Sliding Mode Control — for Constraint Satisfaction and Robustness

Scheduled for presentation during the Contributed session "Variable Structure/ Sliding-mode Control" (TuBT7), Tuesday, October 22, 2013, 14:10−14:30, Room 138

6th Annual Dynamic Systems and Control Conference, October 21-23, 2020, Stanford University, Munger Center, Palo Alto, CA

This information is tentative and subject to change. Compiled on April 19, 2024

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.