Fuzzy Fault-Tolerant Control Design for Intelligent Vehicles

This study examines the development of a fault-tolerant control (FTC) algorithm for intelligent vehicles using a Takagi-Sugeno (TS) fuzzy model. The vehicle is a very intricate nonlinear system, making it challenging to design FTC algorithms. One effective option is to construct a TS fuzzy model for the vehicle's nonlinear system. This model can minimize the computing burden and accurately estimate the vehicle's state. Furthermore, the implementation of a feed-forward and feedback combination controller in the vehicle system enhances system stability, decreases response time, and enhances the reliability and efficiency of vehicle operation. The state feedback FTC algorithm is developed to regulate vehicle dynamics by employing feedback signals from the vehicle's state variables. This algorithm is validated through a high-fidelity Simulink simulation, which is used to determine the state feedback control gain for the vehicle system. The objective is to achieve fault-tolerant control of the vehicle in the event of a failure.