DocumentCode
1111210
Title
Support vector machine networks for friction modeling
Author
Wang, G.L. ; Li, Y.F. ; Bi, D.X.
Author_Institution
Dept. of Electron. & Commun. Eng., Sun Yat-Sen Univ., Guangzhou, China
Volume
9
Issue
3
fYear
2004
Firstpage
601
Lastpage
606
Abstract
This paper presents a novel model-free approach for modeling friction for servo-motion systems. The proposed approach uses the support vector machine networks to parameterize the static friction mapping. The procedure of constructing such networks from a finite amount of training (sampling) data is developed based on support vector machine regression (SVMR). The validity of the proposed approach has been experimentally verified.
Keywords
control system synthesis; linearisation techniques; regression analysis; servomechanisms; stiction; support vector machines; friction modeling; servo motion systems; static friction mapping; support vector machine regression; Adaptive control; Bismuth; Control systems; Estimation error; Friction; Lips; Neural networks; Programmable control; Sampling methods; Support vector machines;
fLanguage
English
Journal_Title
Mechatronics, IEEE/ASME Transactions on
Publisher
ieee
ISSN
1083-4435
Type
jour
DOI
10.1109/TMECH.2004.835345
Filename
1336816
Link To Document