汽车自适应巡航跟车多目标鲁棒控制算法设计

为满足自适应巡航系统跟车模式下的舒适性需求并且兼顾车辆安全性，基于模型预测控制原理提出一种多目标鲁棒跟车控制算法.建立考虑前车加速度干扰的自适应巡航系统车间纵向运动学模型，该模型可全面反映系统的动态演化规律，提高模型的精度和可靠性；针对自适应巡航系统需求进行目标分析，设计一种考虑舒适性和安全性的多目标模型预测控制算法；针对模型预测控制算法鲁棒性较差的问题，引入修正项反馈，提高控制系统鲁棒性，采用向量约束管理法解决模型预测控制算法硬约束造成的控制系统无优化解问题.仿真结果表明：该算法使跟车时车辆加速度及冲击度保持在舒适性范围，同时车间距始终大于最小安全距离，兼顾了舒适性和安全性要求，实现了自适应巡航控制系统跟车目的.
To meet the needs of comfort and take the vehicle safety into account at the same time of car following model of the adaptive cruise control (ACC) system, a multi-objective robust control algorithm of car following model is designed based on model predictive control (MPC) theory. A mutually longitudinal kinematics model considering the pre-car acceleration noise is presented to fully reflect the dynamic evolution of ACC system and improve the model's accuracy and reliability. The target of the requirement of ACC system is analyzed and a multi-objective MPC algorithm considering comfort and safety is proposed. By introducing a correction term feedback, the robustness of the control system is improved for the reason of the MPC algorithm's sensitive to disturbance. By adopting vector management method, the problem is solved which the MPC algorithm can't find the optimum solution caused by hard constraints. The simulation shows that the designed control algorithm ensures that the acceleration and jerk of the ACC system is kept in the comfort range, while the distance between the pre-vehicle and host-vehicle is always greater than the minimum safe distance.