Application of Preview Model Predictive Control Based on Backstepping Contraction Constraints in Autonomous Vehicle Trajectory Tracking

In order to solve the problem of trajectory tracking and stability control of autonomous vehicles in complex scenarios, this paper proposes a cooperative control strategy that integrates predictive control (MPC) and backstepping method with preview information model. In this method, the trajectory prediction accuracy is improved by combining MPC rolling optimization and multi-constraint processing capabilities with preview information, and the shrinkage constraints designed by the backstepping method are integrated into the MPC objective function to improve the convergence of the algorithm. The backstepping controller is constructed based on the vehicle dynamics model, and the Lyapunov stability theory is used to ensure the stability of the global system. The simulation results show that, compared with the traditional MPC, the proposed method improves the trajectory tracking accuracy by 17% and 41% at 30km/h and 45km/h speeds, respectively, and significantly enhances the vehicle stability and algorithm convergence speed, which verifies the effectiveness and superiority of the proposed method in complex driving environments.