基于预见位姿信息的铰接式车辆LQR-GA路径跟踪控制

针对铰接式车辆的特殊转向结构和行驶特性,为提高其路径跟踪控制精度和反应速度,提出了一种基于预见信息的线性二次型最优控制(Linear quadratic regulator,LQR)策略,并应用遗传算法(Genetic algorithm,GA)对状态量权重矩阵进行优化求解,获得最优LQR状态反馈控制器,实现铰接式车辆精确路径跟踪控制,由位置偏差、行驶方位偏差和曲率偏差来反映控制效果。ADAMS-Matlab/Simulink联合仿真结果:位置偏差为0.03 m,偏差误差为1.3%,行驶方位偏差误差为0.19%,曲率偏差收敛于0.003 m-1。联合仿真和试验验证结果表明,所提出的控制方法可有效提高控制精度,实现铰接式车辆的精确、稳定路径跟踪。

LQR-GA Path Tracking Control of Articulated Vehicle Based on Predictive Information

Articulated vehicle is one of the utmost members of intelligent mining equipment and working under terrible conditions, which has the special steering structure and driving characteristics. In order to improve the tracking accuracy and response speed of the articulated vehicle, a linear quadratic regulator (LQR) strategy based on predictive information was proposed and a genetic algorithm (GA) was used to optimize the state quantity matrix, and the optimal LQR state feedback controller was obtained to realize the precise path tracking control of the articulated vehicle. The control result was reflected by the displacement deviation, the heading deviation and the curvature deviation. In the co-simulation (ADAMS-Matlab/Simulink) results, the displacement deviation was 0.03m, the deviation error was 1.3%, the heading deviation error was 0.19%, and the curvature deviation converged to be 0.003m-1. The co-simulation and experiment results showed that the proposed control method can effectively improve the control precision. The control strategy proposed can achieve the precise and stable path tracking of articulated vehicles, which was an alternative control method.