• DocumentCode
    2339269
  • Title

    Non-linear predictive control

  • Author

    Katende, Edward ; Jutan, Arthur

  • Author_Institution
    Dept. of Chem. & Biochem. Eng., Univ. of Western Ontario, London, Ont., Canada
  • Volume
    6
  • fYear
    1995
  • fDate
    21-23 Jun 1995
  • Firstpage
    4199
  • Abstract
    Most predictive control algorithms, including the generalized predictive control (GPC),are based on linear dynamics. Many processes are severely nonlinear and would require high order linear approximations. Another approach, which is presented here, is to extend the basic adaptive GPC algorithm to a nonlinear form. This provides a nonlinear predictive controller which is shown to be very effective in the control of processes with nonlinearities that can be suitably modelled using general Volterra and Hammerstein models and bilinear models. Simulations are presented using a number of examples
  • Keywords
    Volterra equations; nonlinear control systems; predictive control; bilinear models; general Hammerstein models; general Volterra models; nonlinear predictive control; Adaptive control; Control systems; Nonlinear control systems; Polynomials; Prediction algorithms; Predictive control; Predictive models; Programmable control; Temperature control; Thickness control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, Proceedings of the 1995
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-2445-5
  • Type

    conf

  • DOI
    10.1109/ACC.1995.532723
  • Filename
    532723