自动驾驶横向运动控制的改进LQR方法研究

Research on Improved LQR Control for Self-driving Vehicle Lateral Motion

针对自动驾驶横向运动控制问题,提出一种带有前馈控制的改进LQR横向运动控制方法。首先,利用二自由度车辆动力学模型构建了路径跟踪误差动力学模型,设计了自动驾驶LQR控制器以及前馈控制器。随后,针对LQR控制器参数进行分析,提出一种基于路径跟踪误差的参数计算方法和一种基于车-路位置关系的参数调整规则,以此实现LQR控制器的改进,提高控制器的适应性与控制精度。最后,通过Matlab/Carsim联合仿真测试设计的控制器。结果表明,不论是双移线工况还是连续换道工况,设计的控制器均能较好地跟踪目标路径,且能够将距离偏差和航向偏差控制在较小范围内。

In the paper,an improved LQR lateral motion control method with feedforward control is proposed to solve the lateral motion control problem of self-driving vehicle.Firstly,the path tracking error dynamics model is built by using a 2-DOF vehicle dynamics model,and the LQR controller and the feedforward controller are designed based on the path tracking error dynamics model.Secondly,based on the analysis of LQR controller parameters,a parameter calculation method based on path tracking error and a parameter adjustment rule based on vehicle-road position relation are proposed to improve the adaptability and control accuracy of LQR controller.Finally,the designed controller is tested by Matlab/Carsim co-simulation.The simulation results show that the improved LQR controller can track the target path well,and can control the lateral deviation and heading deviation of unmanned vehicle in a small range,whether in double or continuous lane changing conditions.