Iterative Learning Control for Time-Varying Systems Subject to Variable Pass Lengths: Application to Robot Manipulators

• Published in: IEEE transactions on industrial electronics (1982) Vol. 67; no. 10; pp. 8629 - 8637
• Main Authors: Shi, Jiantao, Xu, Jianxin, Sun, Jun, Yang, Yuhao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Gaussian distribution; Indexes; Iterative learning control; Iterative learning control (ILC); Lead; Learning; Manipulators; Normal distribution; Randomness; Robot arms; robot manipulator; stochastic time-varying systems; Time varying control systems; Time-varying systems; Tracking errors; variable pass lengths
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2019.2947838

In this article, the iterative learning control (ILC) problem is investigated for a class of stochastic time-varying systems with variable pass lengths. The randomness of the pass lengths is described by the recursive interval Gaussian distribution, and a modified iteration-average operator is developed to construct the novel ILC scheme for overcoming the limitation of conventional ILC algorithms that every pass must end in a fixed time of duration throughout the repetition. The proposed ILC approach works effectively to guarantee the boundedness of the tracking errors, which is demonstrated by a practical case study on a type of robot manipulator with two joints.