DocumentCode
1007512
Title
Neural network based friction compensation in motion control
Author
Ciliz, M.K. ; Tomizuka, M.
Author_Institution
Electr. Eng. Dept., Bogazici Univ., Istanbul, Turkey
Volume
40
Issue
12
fYear
2004
fDate
6/10/2004 12:00:00 AM
Firstpage
752
Lastpage
753
Abstract
Frictional uncertainties are known to be a major cause of performance degradation in motion control systems. Artificial neural network based modelling and compensation of nonlinear friction in direct drive servo mechanisms have been investigated. The proposed method is successfully tested experimentally on a direct-drive single-link arm and its performance is compared to different friction modelling techniques.
Keywords
compensation; feedforward neural nets; friction; mechanical variables control; motion control; multilayer perceptrons; neurocontrollers; servomechanisms; artificial neural network based modelling; direct drive servo mechanisms; direct drive single link arm; friction modelling techniques; motion control systems; nonlinear friction compensation; performance degradation;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:20040500
Filename
1305483
Link To Document