Detail View

Reduced-Order Nominal Model Design and Validation For Task Space DOB-Based Motion Control of An Industrial Robot
Citations

WEB OF SCIENCE

Citations

SCOPUS

Metadata Downloads

Title
Reduced-Order Nominal Model Design and Validation For Task Space DOB-Based Motion Control of An Industrial Robot
Issued Date
2023-06-30
Citation
Samuel, Kangwagye. (2023-06-30). Reduced-Order Nominal Model Design and Validation For Task Space DOB-Based Motion Control of An Industrial Robot. IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2023, 1095–1101. doi: 10.1109/AIM46323.2023.10196253
Type
Conference Paper
ISBN
9781665476331
ISSN
2159-6255
Abstract
In conventional robust motion control systems, disturbance observer (DOB) nominal models are designed with same order as the actual plant such that the nominal model directly cancels with the actual plant dynamics. However, for multi-DOF systems such as 6-DOF industrial robots, identifying the higher-order model is laborious. Moreover, there is a high risk of obtaining a nominal model with large deviation from the actual plant due to severe parameter uncertainty. Thus, a reduced-order nominal model is derived from the actual plant model and compared with the one which same order as the actual plant in this paper. The designed model is simple, easy to identify and implement. From the analyses and experiment results, DOB with the proposed nominal model is not affected by severe robot model uncertainty and show significant improvement in motion control performance in terms of transient response and tracking accuracy. © 2023 IEEE.
URI
http://hdl.handle.net/20.500.11750/47921
DOI
10.1109/AIM46323.2023.10196253
Publisher
IEEE Robotics and Automation Society (RAS), IEEE Industrial Electronics Society (IES), ASME Dynamic Systems and Control Division (DSCD)
Show Full Item Record

File Downloads

  • There are no files associated with this item.

공유

qrcode
공유하기

Related Researcher

오세훈
Oh, Sehoon오세훈

Department of Robotics and Mechatronics Engineering

read more

Total Views & Downloads