Robust two-degree-of-freedom iterative learning control for flexibility compensation of industrial robot manipulators
Document Type
Conference Proceeding
Publication Date
6-8-2016
Abstract
Most industrial robots are actuated using geared motors with no direct load side measurement. The flexibility introduced by the gear reducer causes transmission errors and vibrations, which limits the adoption of robot manipulators in many demanding applications. This paper presents a lean and efficient scheme of iterative learning control (ILC) to compensate for the joint flexibility of industrial robot manipulators. A two-degree-of-freedom ILC method is introduced. Compared with the dual-stage ILC that has been previously proposed for servo flexibility compensation, the method is more effective and also enables a leaner implementation. In addition, in order to handle system variation, a robust synthesis method is developed by using H∞ and μ techniques in an innovative way. The proposed method is analyzed using simulation studies as well as tested on an actual industrial robot manipulator.
Identifier
84977559833 (Scopus)
ISBN
[9781467380263]
Publication Title
Proceedings IEEE International Conference on Robotics and Automation
External Full Text Location
https://doi.org/10.1109/ICRA.2016.7487388
ISSN
10504729
First Page
2381
Last Page
2386
Volume
2016-June
Recommended Citation
Wang, Cong; Zheng, Minghui; Wang, Zining; and Tomizuka, Masayoshi, "Robust two-degree-of-freedom iterative learning control for flexibility compensation of industrial robot manipulators" (2016). Faculty Publications. 10446.
https://digitalcommons.njit.edu/fac_pubs/10446
