Adaptive Fixed-Time Path Tracking Control for Autonomous Vehicles Subject to Full State Constraints and Unknown Tire Cornering Stiffness

This paper investigates the problem of path tracking for autonomous vehicles subject to unknown tire cornering stiffness and full state constraints. First, by analyzing the effects of nonlinear tire dynamics on path tracking performance, the tire cornering stiffnesses are treated as unknown parameters in the modeling process, which contributes to improving the robustness of the vehicle control system. Second, to handle the unknown tire cornering stiffness in system matrices and control coefficients, an adaptive fixed-time path tracking control strategy with high-gain observer-based output feedback is developed. Different from the existing methods, the lower bounds of unknown control coefficients are incorporated into the Lyapunov function to effectively eliminate the requirement of tire cornering stiffness and their bounds information. Moreover, the full state constraints, formulated based on the vehicle stability margins, are taken into account to enhance the dynamic stability of the vehicle. Based on the barrier Lyapunov stability theory, it is proven that the designed adaptive backstepping controller guarantees the fixed-time stability of the closed-loop system, and that all vehicle states remain within the constraints of stability region. Finally, the effectiveness of the proposed control scheme is demonstrated through simulation and comparison results.