Intelligent automobile path tracking control based on T-S fuzzy

Abstract

To coordinate the accuracy and driving stability of intelligent automobile in the path tracking process and improve the adaptive capability of the control algorithm to different working conditions, an intelligent automobile path tracking control method based on T-S fuzzy is proposed. First, the lateral deviation and heading angle deviation during tracking are considered, and the path tracking error equation is established using a 2 degree-of-freedom single-track dynamic model. Second, an adaptive preview algorithm based on vehicle speed, reference path curvature and heading angle deviation is designed, and feedforward control is designed based on the results of the algorithm. Then, the T-S fuzzy control method with fast decision-making capability is utilized to realize the adaptive adjustment of the weight coefficients of the linear quadratic regulation (LQR) controller to adapt to the variable weight path tracking control under different working conditions. Finally, the designed control method is tested on a double-lane road condition using the Carsim-Simulink co-simulation platform. The results show that the designed controller has high tracking accuracy, and can maintain good accuracy and driving stability under different working conditions.