DocumentCode
295014
Title
Tuning convergence rate of a robust learning controller for robot manipulators
Author
Kuc, Tae-Yong ; Lee, Jin S. ; Park, Byung-Hyun
Author_Institution
Dept. of Electron. Eng., Sung Kyun Kwan Univ., Suwon, South Korea
Volume
2
fYear
1995
fDate
13-15 Dec 1995
Firstpage
1714
Abstract
This paper presents a robust learning control algorithm which learns the entire span of robot trajectory within a finite time interval. The learning controller treats the uncertain parameters as well as unknown external disturbances with the aid of the linear parameterization property of the robot system and robust feedback control input. It is shown that the robot motion converges exponentially to the desired one as the iteration continues
Keywords
convergence; feedback; learning systems; manipulators; motion control; robust control; tuning; linear parameterization property; robot manipulators; robot motion; robot trajectory; robust feedback control input; robust learning controller; tuning convergence rate; unknown external disturbances; Adaptive control; Control systems; Convergence; Feedback control; Manipulator dynamics; Robot control; Robot kinematics; Robot motion; Robust control; Symmetric matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location
New Orleans, LA
ISSN
0191-2216
Print_ISBN
0-7803-2685-7
Type
conf
DOI
10.1109/CDC.1995.480387
Filename
480387
Link To Document