Title
Gain-Scheduled Drive-based Damping Control for Industrial Robots
Abstract
The drivetrain flexibility of industrial robots limits their accuracy. To open up new areas of application for industrial robots, an increased dynamic path accuracy has to be obtained. Therefore, this paper addresses this issue by a gain-scheduled drive-based damping control for industrial robots with secondary encoders. For this purpose, a linear parameter-varying (LPV) model is derived as well as a system identification method is presented. Based on this, a gain-scheduled drive-based LPV damping control design is proposed, which guarantees stability and performance under variation of the manipulator configuration. The control performance of the approach is experimentally validated for the three base joints of a KUKA KR210-2 industrial robot. The approach realizes a trade-off between ease of implementation and control performance as well as robustness.
Year
DOI
Venue
2022
10.1109/AIM52237.2022.9863417
2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)
Keywords
DocType
ISSN
Motion control,flexible joint robots,linear parameter varying,structured H-infinity synthesis
Conference
2159-6247
ISBN
Citations 
PageRank 
978-1-6654-1309-1
0
0.34
References 
Authors
16
4
Name
Order
Citations
PageRank
Patrick Mesmer121.39
Christoph Hinze200.34
Armin Lechler301.01
Alexander Verl411.38