自适应模型预测控制的车道保持控制策略

建立车辆侧向动力学模块、车辆传感模块、道路曲率预瞄模块.在传统模型预测控制(MPC)算法的基础上,利用辛普森法则,结合车道保持优化性能指标和系统约束,设计基于自适应模型预测控制的车道保持控制策略.在Simulink环境下,将其与基于传统模型预测控制器进行比较分析.仿真结果表明:相较于模型预测控制,自适应MPC能够在各控制周期实现车辆模型更新,在强非线性工况下具备较好的鲁棒性,进而能够保证行车安全的前提下,获取较好的乘坐舒适性.

Lane Keeping Control Strategy Based on Adaptive Model Predictive Control

Vehicle lateral dynamics module, vehicle sensing module and road curvature preview module were established. Based on the traditional model predictive control(MPC)algorithm, using Simpson’s law, combined with lane keeping optimization performance index and system constraints, a lane keeping control strategy based on adaptive model predictive control was designed and compared with the traditional model predictive controller in Simulink environment. The simulation result shows that compared with the model predictive control, the adaptive MPC can update the vehicle model in each control cycle, has better robustness under strong non-linear conditions, and can obtain better ride comfort under the premise of ensuring driving safety.