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 :
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