Robust Takagi–Sugeno Fuzzy Fault Tolerant Control for Vehicle Lateral Dynamics Stabilization With Integrated Actuator Fault and Time Delay

Abstract

This paper investigates the lateral dynamics stabilization problem for autonomous electric vehicles (AEVs) through the active front steering (AFS) system. A fault-estimation-observer-based robust fuzzy fault tolerant controller is proposed to tackle actuator faults, time delay, modeling nonlinearities, and external disturbances. First, to establish a more accurate dynamics model, the Takagi–Sugeno (T–S) fuzzy modeling strategy is utilized to handle velocity change and parameter uncertainties. Second, to further improve the lateral stability and driving active safety of the AEV, an integrated actuator fault model comprising efficiency loss fault and additional bias fault is proposed. Meanwhile, in order to diagnose actuator additional bias fault, a fuzzy fault estimation observer (FFEO) is designed to acquire fault information online. Third, to eliminate the influence caused by integrated fault and actuator time delay, a fuzzy fault tolerant controller is constructed to improve the handling performance and driving active safety of the AEV. Finally, the effectiveness of the proposed control scheme is demonstrated via a full-car model based on the joint simulation of carsim and matlab/simulink.