机械臂动力学前馈混合迭代学习控制研究OA

In response to the problems in manipulator trajectory tracking control,including inaccurate dynamic parameters and unknown external disturbances,a control method integrating dynamic feedforward with iterative learning is proposed.Firstly,dynamic feedforward control was employed to enable the manipulator to achieve basic tracking of the desired trajectory,and the control system equations were linearized within a small vicinity of the desired trajectory.Subsequently,an iterative learning controller was introduced to mitigate the impact of inaccuracies in dynamic parameters and external disturbances.Through iterations,it further reduced the trajectory tracking errors.The error convergence of the present control scheme was analyzed by using a compression mapping approach.The simulation experiments were conducted by using M WORKS.Sysplorer platform,and the experiments were performed on a six-axis serial-link manipulator.The results indicated that the present approach,through iterative learning,gradually reduced the trajectory tracking errors of the manipulator.