基于模糊控制的插秧机LQR曲线路径跟踪控制器优化方法

Optimization Method of LQR Curve Path Tracking Controller for Unmanned Rice Transplanter Based on Fuzzy Control

为了提高无人插秧机地头转向时的曲线路径跟踪精度,针对传统的误差权重矩阵固定的线性二次调节器(Linear quadratic regulator,LQR)路径跟踪控制器对插秧机的纵向速度、横向偏差以及航向角偏差的变化适应性较差的问题,基于车辆二自由度动力学模型,提出了一种通过模糊控制实时调整LQR控制器误差权重矩阵的路径跟踪控制器优化方法。该方法以纵向速度、横向偏差、航向角偏差为输入,以横向偏差和航向角偏差对应的误差权重为输出,建立模糊控制模型实时调整LQR控制器的误差权重矩阵。为了验证所提出算法的曲线路径跟踪控制精度和可行性,以改装后的洋马VP6E型无人插秧机为对象,进行Carsim和Simulink联合仿真试验以及实车试验。仿真试验结果表明,在控制插秧机跟踪半径为2 m的1/4圆弧路径时,所提出算法控制下的横向偏差绝对值均值为0.014 m,最大值为0.032 m,小于0.04 m的占100%,航向角偏差绝对值均值为1.67°,最大值为4.94°,相较于传统引入前馈控制的LQR控制器,横向偏差绝对值均值降低50%,航向角偏差绝对值均值降低23%。实车试验结果表明,在插秧机跟踪半径为2 m的1/4圆弧路径时,所提出算法控制下横向偏差绝对值均值为0.027 m,最大值为0.048 m,小于0.04 m的占62%,航向角偏差绝对值均值为1.86°,最大值为4.94°,相较于传统引入前馈控制的LQR控制器,横向偏差绝对值均值降低40%,航向角偏差绝对值均值降低4.1%。该方法提升了无人插秧机曲线路径跟踪控制精度,为无人插秧机曲线路径跟踪控制提供了参考。

The precision of curve path tracking affects the efficiency of unmanned rice transplanter by affecting the efficiency of line changing.In order to improve the curve path tracking accuracy of the unmanned rice transplanter when turning from the headland,in view of the poor adaptability of the traditional linear quadratic regulator(LQR)path tracking controller with fixed error weight matrix to the changes of the longitudinal speed,lateral deviation and heading angle deviation of the rice transplanter,an optimization method of path tracking controller by adjusting the error weight matrix of linear quadratic regulator in real time through fuzzy control was presented.The method took the longitudinal speed,lateral deviation and heading angle deviation as the input,and the error weight corresponding to the lateral deviation and heading angle deviation as the output,and a fuzzy control model was established to adjust the error weight matrix of the linear quadratic regulator in real time.In order to verify the accuracy and feasibility of the curve path tracking control of the proposed algorithm,the refitted Yangma VP6E unmanned rice transplanter was taken as the object,and Carsim and Simulink joint simulation tests and real vehicle tests were carried out.The simulation test results showed that when the rice transplanter was controlled to track a quarter arc path with radius of 2 m,the average value of absolute value of lateral deviation under the control of the proposed algorithm was 0.014 m,the maximum value was 0.032 m,and 100%of those were less than 0.04 m,the average value of the absolute value of heading angle deviation was 1.67°,and the maximum value was 4.94°.Compared with the traditional linear quadratic regulator with feedforward control,the average value of absolute value of lateral deviation was reduced by 50%,the average absolute value of heading angle deviation was decreased by 23%.The real vehicle test results showed that when the rice transplanter tracked a quarter arc path with radius of 2 m,the average value of the absolute value of lateral deviation under control of proposed algorithm was 0.027 m,the maximum value was 0.048 m,and 62%of those were less than 0.04 m,the average value of absolute value of heading angle deviation was 1.86°,and the maximum value was 4.94°.Compared with the traditional linear quadratic regulator with feedforward control,the average value of absolute value of lateral deviation was reduced by 40%.The average absolute value of heading angle deviation was decreased by 4.1%.The method improved the curve path tracking control accuracy of the unmanned rice transplanter,and provided a reference for the curve path tracking control of the unmanned rice transplanter.