Robust Performance Tracking Control for Vehicles Based on Sliding Mode

Abstract

 To solve the parameter uncertainty and external disturbance in vehicle trajectory tracking control, this paper proposes a cooperative control architecture based on predictive performance function (PPF) and terminal sliding mode control (TSMC). By constructing a time-varying performance function, dynamically constraining the transient and steady-state performance of the tracking error, and combining the finite-time convergence characteristics of the non-singular terminal sliding surface, this method realizes the global robust adjustment of the tracking error within the preset performance boundary. Lyapunov theory proves the finite-time stability of the closed-loop system and verifies the effectiveness of the cooperative mechanism between PPF and TSMC in suppressing parameter perturbation and external disturbance. According to Simulink simulation results, compared with traditional TSMC and preset performance control strategies, the method proposed in this paper manifests better tracking accuracy and dynamic robustness, which provides the theoretical basis and engineering references for trajectory tracking control of intelligent vehicles in complex environments.