采用状态反馈的无人车路径跟踪横向控制

A Lateral Control Strategy for Unmanned Vehicle Path Tracking using State Feedback

针对采用传统模型预测控制器的车辆在弯道内跟踪精度难以保证的问题,本文提出了一种基于状态反馈的路径跟踪横向控制策略。基于车辆动力学模型,建立考虑轮胎滑移包络线约束条件的路径跟踪模型预测控制器,并根据车速选择合适的控制器时域参数;以车辆质心位置为控制点建立车辆跟踪误差模型,结合车辆当前位置横摆角偏差建立状态反馈调节器,通过LQR最优控制方法对无人车姿态进行校正。利用MATLAB/Simulink和Carsim软件对改进的状态反馈控制策略进行了仿真验证,典型双移线道路仿真试验表明:中低车速下车辆路径跟踪横向偏差降低了16%以上,横摆角偏差降低了33%以上,所设计控制器能够有效提高车辆路径跟踪精度,可保证车辆对变曲率弯道具有适应性和行驶稳定性。

Because it is difficult to guarantee the tracking accuracy of an unmanned vehicle in its bending path with the traditional model predictive controller,this paper proposes a lateral control strategy for the path tracking based on state feedback.Based on the vehicle dynamics model,the path tracking model predictive controller that considers the constraints of the tire slip envelope of the unmanned vehicle is established,and the appropriate time-domain parameters of the controller are selected according to the speed of the unmanned vehicle;its tracking error model is established by using the centroid position of the vehicle as control point.The state feedback regulator is established by combining the yaw angle deviations of the current position of the vehicle,and the attitude of the unmanned vehicle is corrected with the LQR optimal control method.The improved state feedback control strategy is simulated and verified with the MATLAB/Simulink software and the Carsim software.The typical double lane change simulation results show that the lateral deviation of the vehicle′s path tracking is reduced by more than 16%and the yaw angle deviation is reduced by 33%at low and medium speeds.Above all,the controller improved in the paper can effectively improve the path tracking accuracy and ensure the adaptability and driving stability of an unmanned vehicle on various curvature bends.