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

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