• DocumentCode
    2437198
  • Title

    Adaptive control of a class of nonlinear systems using Support Vector Regression

  • Author

    George, Koshy ; Harshangi, Prashanth

  • Author_Institution
    E.E.S. Centre for Intell. Syst., Bangalore, India
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    311
  • Lastpage
    316
  • Abstract
    In this paper we demonstrate an improvement in the transient tracking performance when a Support Vector Regression (SVR) is used to identify a nonlinear ARMA plant. We use an on-line version of SVR, and at each instant, the identified model is used to determine the appropriate control law. A further improvement in the transient performance is shown with the methodology of multiple models, switching, and tuning.
  • Keywords
    adaptive control; control system synthesis; nonlinear control systems; regression analysis; support vector machines; adaptive control; nonlinear ARMA plant; nonlinear systems; support vector regression; transient tracking performance; Adaptation model; Adaptive control; Artificial neural networks; Nonlinear systems; Support vector machines; Training; Transient analysis; Adaptive systems; NARMA; multiple models; support vector regression; switching and tuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-7814-9
  • Type

    conf

  • DOI
    10.1109/ICARCV.2010.5707793
  • Filename
    5707793