基于模型预测和转角补偿的智能汽车换道轨迹跟踪控制算法

Trajectory tracking control algorithm of lane changing for intelligent vehicle based on model prediction and angle compensation

为了提高自动驾驶跟踪过程中路径跟踪的精确性和车辆的操纵稳定性,提出了一种基于模型预测控制原理并结合转角补偿的轨迹跟踪控制方法.将整体控制结构分为上下两层:上层为轨迹跟踪控制层,根据获得的道路信息及车辆行驶状态,利用模型预测控制算法得出车辆的前轮转角控制量;下层采用滑模控制理论设计转角补偿器,以汽车的横摆角速度误差为控制目标,实现精确跟踪.结果表明:与单点预瞄策略相比,模型预测+转角补偿的轨迹跟踪控制策略能更好地控制车辆实现轨迹跟踪,且横摆角速度和质心侧偏角峰值明显降低,稳定性更好.

To improve the accuracy of path tracking and the vehicle handling stability in the process of automatic driving tracking,a trajectory tracking control method based on model predictive control principle and angle compensation was proposed.The overall control structure was divided into two layers,and the upper layer was the trajectory tracking control layer.According to the obtained road information and the driving state of the vehicle,the front wheel steering control input was determined by the model predictive control algorithm.In the lower layer,the sliding mode control theory was used to design the angle compensator,and the yaw rate deviation of the vehicle was taken as the control target to achieve accurate tracking.The results show that compared with the single-point preview strategy,the trajectory tracking control strategy based on model prediction and angle compensation can better control the vehicle to achieve trajectory tracking,and the peak values of yaw rate and sideslip angle are significantly reduced with better stability.