Lateral Controller for Autonomous Vehicle Path Tracking Based on MPC-SMC Dual Model System

The accuracy of the path tracking process of autonomous vehicles is influenced by the instability of a single controller, resulting in large tracking errors. To tackle this problem, this paper proposes a lateral controller based on the joint action of model predictive control (MPC) and sliding model control (SMC). At first, a six-degree-of-freedom vehicle dynamics model is established and a path tracking controller is designed based on MPC. To enhance the robustness of the controller, a preview driver model utilizing SMC is integrated. Furthermore, the parameters of the SMC are optimized via a differential evolution (DE) and the constraints on the tire slip angle are added to the traditional MPC to facilitate the stability under moving condition. Finally, the control system is verified by co-simulation of Matlab/Simulink and CarSim and the simulation results demonstrate that the proposed controller could provide excellent control accuracy and strong robustness.