Variable-Horizon Model Predictive Control for Switched Systems

Abstract

This paper investigates model predictive control (MPC) for switched systems subject to control and state constraints. A variable-horizon switched MPC approach is proposed. By steering the system state into a well-designed switching feasible set, the proposed method structurally decouples the dwell-time conditions from the MPC constraints, thereby relaxing the dwell-time requirements to match those of the unconstrained switched systems. Furthermore, algorithms are developed to construct this switching feasible set and characterize the domain of attraction, ensuring both persistent feasibility and closed-loop asymptotic stability. To further decouple the prediction horizon length from strict dwell-time bounds, advanced short-horizon switched MPC schemes are designed, which expand the overall domain of attraction. Simulations illustrate the efficacy of the proposed methods.