A SORT OF ITERATIVE LEARNING CONTROL ALGORITHM FOR TRACKING OF ROBOT TRAJECTORY
Yao Zhongshu Wang Hongfei Yang Chengwu (Nanjing University of Science and Technology, Nanjing, 210094)
An iterative learning control with forgetting factors for the tracking of robot trajectories was proposed, and conditions were presented to guarantee convergence of the iterative algorithm. The convergence of error can be improved without modifying the structure of the controller by utilizing previous experience in tracking different desired trajectories to select an initial control input for a new desired trajectory tracking. The output of the system can track the desired trajectory better. A simulation shows the fast convergence of the proposed algorithm.
【CateGory Index】： TP24;TP27