Robust Adaptive Sliding Mode Control for Nonlinear Four-Wheel Steering Autonomous Vehicles Path Tracking Systems

This paper researches the nonlinear four-wheel steering (4WS) autonomous Vehicles (AVs) path tracking systems using robust adaptive sliding mode controller. Considering control input nonlinearity, and the parameter-varying property of tire cornering stiffness in extreme handling situations, a Takagi-Sugeno (T-S) fuzzy model is established to represent the nonlinear characteristics of tires and control input nonlinearity. A robust adaptive sliding mode controller is designed to achieve the path tracking and vehicle lateral control simultaneously. The condition of the control constraint can be converted to the H-infinity/H-2 convex optimization problem. Two simulation cases are presented with a high-fidelity and full-car model based on the CarSim-Simulink joint platform, and the results confirm the effectiveness of the proposed control approach.