TVIE-based fault-tolerant model predictive control for trajectory tracking of mobile robot

Abstract

This paper investigates the trajectory tracking control issue for a linear parameter-varying (LPV) system of a wheeled mobile robot (WMR) with actuator fault and constraints, where a time-varying intermediate estimator (TVIE)-based fault-tolerant model predictive control (MPC) method is proposed. To obtain the real system with actuator fault, based on the existing traditional IE, an optimized objective function is designed to update its observer gain online, which results in a TVIE. A new estimation-based predictive model in MPC is designed by introducing the estimations of error state and fault from the TVIE. Moreover, compared with the existing IE or extended state observer (ESO), the estimation performance of TVIE is better. Then the MPC optimization strategy is used to design fault-tolerant controllers. To guarantee stability and recursive feasibility, the bimodal MPC strategy is used, where a terminal penalty and a terminal constraint are included. Finally, the effectiveness and superiority of the proposed approach is illustrated in experiment.