Switched model predictive controller for path tracking of autonomous vehicle considering rollover stability
Ying Tian, Qiangqiang Yao, Chengqiang Wang, Shengyuan Wang, Jiaqi Liu, Qun Wang
Abstract
Lateral stability and rollover stability are two most crucial concerns for path tracking of an autonomous vehicle under handling limit conditions. To improve path tracking accuracy and ensure vehicle stability under handling limit conditions, this paper proposes a force-driven switched MPC path tracking control strategy that coordinates active front-wheel steering with an external yaw moment. Firstly, a linear time-varying tire model is modelled using the affine approximate linearisation method to describe rear tire dymamics. And vehicle dynamics is modelled to predict vehicle states in the prediction horizon. Then, a force-driven switched MPC control strategy is proposed based on the system prediction model. The vehicle lateral stability and rollover stability are restricted using maximum tire lateral force and the zero-point moment method, respectively. Finally, according to the simulation results under normal speed and limiting speed conditions, a force-driven switched MPC control strategy can improve control accuracy and ensure vehicle stability.