Robust Fault Estimation and Fault‐Tolerant Control in T–S Fuzzy Systems Using H∞$$ {H}_{\infty } $$ Optimization: Application to Lateral Vehicle Dynamics

Abstract

ABSTRACT This paper proposes an integrated observer‐based fault estimation (FE) and fault‐tolerant control (FTC) framework for discrete‐time Takagi–Sugeno (T–S) fuzzy systems subject to actuator faults, external disturbances, and parametric uncertainties. A robust fuzzy observer reconstructs the system states and actuator faults, and these estimates drive a state‐feedback controller that compensates for faults online while ensuring a prescribed performance. Sufficient linear matrix inequality (LMI) conditions derived using a Lyapunov–Krasovskii functional (LKF) and Finsler's lemma enable tractable synthesis of both the observer and the controller. The method was applied to a lateral vehicle model, which has uncertainties, disturbances, and sudden actuator faults. The results obtained demonstrate that the closed‐loop system was stable and made accurate tracking. The results of the method implemented showed accurate estimator performance and robust compensation under faults, which should be highlighted by the credible performance when used in closed loop. The results show that the method has practical application for safety‐critical nonlinear systems.