• 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