Reduced-Order Estimator-Based Efficient Fault-Tolerant Tracking Control Optimization for Constrained LPV Systems

Abstract

This article focuses on addressing a fault-tolerant tracking control (FTTC) problem for a class of constrained polytopic LPV systems. The dual-mode predictive control method is introduced to design an efficient FTTC strategy such that the performance output of LPV systems can be regulated to track a given reference within state/input constraints. On the whole, the FTTC policy is constructed by the reduced-order estimator, tracking error feedback, double signal compensation, and optimal predictive regulation (PR). In specific, a novel reduced-order estimator is first designed to provide the state and fault information. Then, an unconstrained robust tracking error feedback control is designed to stabilize the LPV systems. Following that, a double signal compensation mechanism is proposed to remove the influences of fault, fault estimation error and other mismatched disturbances. Afterward, an optimal PR policy is further designed to optimize the tracking performance and handle system constraints. Finally, the effectiveness of these proposed results is verified by three case studies.