Model Predictive Control of Uncertain Switched Systems with A Linear Nominal Model

Abstract

This paper presents the model predictive control of an uncertain linear switched system that includes external disturbance, parametric uncertainty, and generally, every uncertainty due to modeling error. Model Predictive Control (MPC) has been efficiently applied to certain systems as an optimal control. Since the MPC is model-based, there are difficulties in applying the MPC procedure to uncertain switched systems with linear nominal models. To overcome these problems, this paper presents a novel optimal control of uncertain switched systems with linear nominal models. For this purpose, a control-oriented model is introduced to apply the proposed MPC while the modeling error is estimated and compensated by a robust time-delay controller. Then MPC is performed for designing the control input and switching the signal. The proposed control design is verified by a stability analysis. The simulation results on a mass-spring-damper system verify the effectiveness of the proposed control approach.