基于自适应预瞄的履带式无人车轨迹预测控制

Research on adaptive trajectory tracking control of tracked unmanned vehicle based on sliding parameter estimation

针对履带式无人车采用纯跟踪算法进行轨迹跟踪控制时轨迹适应能力差及跟踪精度低等问题,提出了基于轨迹预测的自适应预瞄跟踪控制算法。首先建立基于瞬时转向中心的运动学模型,并基于该模型和无迹卡尔曼滤波算法对履带式无人车进行滑动参数估计及轨迹预测;然后构造代价函数,利用轨迹预测结果在多个预瞄点中选择代价最小的预瞄点用于无人车纯跟踪控制;最后利用Simulink/Recurdyn进行仿真。结果表明,该算法可有效提高纯跟踪控制器的控制效果。

The pure pursuit algorithm has poor trajectory adaptation capability and low tracking accuracy.To solve the above problems,a adaptive prepursuit algorithm is proposed.Firstly,the kinematic model of tracked unmanned vehicle is carried out,and the location of instantaneous centers of rotation of tracked vehicle is found based on UKF algorithm,and the vehicle trajectory is predicted based on the location of instantaneous centers of rotation of tracked vehicle;then,it builds the cost function and uses the trajectory prediction information to select the looking-ahead point with the smallest cost function value among multiple looking-ahead points for the unmanned vehicle pure tracking control.Finally,Simulink/Recurdyn is used to simulate the above contents,and the simulation proves that the algorithm can effectively improve the control effect of pure-pursuit controller.