• DocumentCode
    2626423
  • Title

    Parameter estimation for the LuGre friction model using interval analysis and set inversion

  • Author

    Madi, M.S. ; Khayati, Karim ; Bigras, P.

  • Author_Institution
    Dept. of Autom. Manuf. Eng., Ecole de Technol. Superieure, Montreal, Que., Canada
  • Volume
    1
  • fYear
    2004
  • fDate
    10-13 Oct. 2004
  • Firstpage
    428
  • Abstract
    The purpose of This work is to use bounded error estimation (BEE) approach based on interval analysis and set inversion in order to obtain guaranteed estimation interval for the LuGre friction model parameters. The method assumes that if the errors corrupting the measurements are available and bounded, then the set of all parameters, which are consistent with data output, and these errors (uncertainties) are computed. The main advantage of this method in comparison with the classical ones, as the least square (LS) approach, is that it provides not only the estimate of the parameters but also the precision with which the estimated values is obtained. Moreover, as it´s global, it bypasses the problem of initialization. To validate the proposed approach, experimental data are collected from an actuating electro-pneumatic device, and are used to estimate the friction parameters.
  • Keywords
    boundary-value problems; friction; least mean squares methods; parameter estimation; set theory; LuGre friction model; actuating electropneumatic device; boundary value problems; bounded error estimation; interval analysis; least square method; parameter estimation; set inversion; Boundary value problems; Error analysis; Friction; Least squares approximation; Manufacturing automation; Parameter estimation; Pulp manufacturing; Signal processing algorithms; Uncertainty; Virtual manufacturing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2004 IEEE International Conference on
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-8566-7
  • Type

    conf

  • DOI
    10.1109/ICSMC.2004.1398335
  • Filename
    1398335