Title
Robust Learning Control for Robot Manipulators With Random Initial Errors and Iteration-Varying Reference Trajectories.
Abstract
In this paper, we propose an error-tracking iterative learning control scheme to tackle the position tracking problem for robot manipulators with random initial errors and iteration-varying reference trajectories. Different from general usual ones, the control strategy in our work is to drive system errors perfectly track the desired error trajectories over the whole time interval as the iteration number increases, by which, the position trajectory and velocity trajectory can respectively track their reference trajectories during the predefined part operation interval. For fulfilling the control design, a new construction method of desired error trajectories is presented to remove the perfect initial resetting condition, which must be satisfied in most traditional iterative learning control algorithms. The uncertainties and disturbances in the robotic system dynamics are compensated by the robust approach and iterative learning approach, combinedly.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2904171
IEEE ACCESS
Keywords
Field
DocType
Iterative learning control,initial problem,robot manipulators
Robotic systems,Computer science,Control theory,Robust learning,Iterative learning control,Robot manipulator,Construction method,Trajectory,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yuan-Ming Ding122.09
Jianping Cai221221.57
Yan Ma343776.23
Youfang Yu401.01