• DocumentCode
    581695
  • Title

    Iterative Learning Control of hysteresis nonlinearity system

  • Author

    Wei, Wang ; Xinlong, Zhao

  • Author_Institution
    Coll. of Mech. Eng. & Autom., Zhejiang Sci-Tech Univ., Hangzhou, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    1070
  • Lastpage
    1072
  • Abstract
    Hysteresis nonlinearity can result in the degradation of system performance and even lead to instability. A control method based on ILC (Iterative Learning Control) is proposed to control the nonlinear system with hysteresis. First, appropriate updating law is selected to design the ILC controller. Then optimal control signal is chosen by means of iterative learning. Finally, the system output can continually converge to the expectation. This method has good performance and can improve the precision of system. The simulation result shows the effectiveness of the proposed method.
  • Keywords
    control nonlinearities; hysteresis; iterative methods; learning systems; optimal control; stability; ILC; hysteresis nonlinearity system; instability; iterative learning control; nonlinear system; optimal control signal; system performance degradation; updating law; Control systems; Fuzzy systems; Hysteresis; Mechatronics; Precision engineering; hysteresis; iterative learning; updating law;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2012 31st Chinese
  • Conference_Location
    Hefei
  • ISSN
    1934-1768
  • Print_ISBN
    978-1-4673-2581-3
  • Type

    conf

  • Filename
    6390083