Adaptive Higher-Order Sliding Mode Control Based Fuzzy Logic T-S for Lateral Dynamics of Autonomous Vehicles

Abstract

In this paper, we have used the super-twisting sliding mode control to control the lateral dynamics of the autonomous vehicle. We approximate the equivalent command used to control the autonomous vehicle by fuzzy logic type Takagi-Sugeno and also we optimize the parameters of this controller using the optimization of the particle swarm (PSO) to improve the performance of this control. And more specifically we used fuzzy logic by combining the adaptive control mechanism based on Lyapunov stability theory to approximate the equivalent control. In these studies we propose a control method without knowledge of the dynamics of the automobile vehicle system based on the use fuzzy logic technique type Takagi-Sugeno (T-S). The goal of this controller is that the autonomous vehicle becomes able to follow the reference trajectory and reduce the lateral displacement error as much as possible. The command is the steering angle, the lateral displacement is the output of this system which depends on the variation of the yaw angle. The simulation results obtained by our proposed controller are better.