• DocumentCode
    453781
  • Title

    U-model based adaptive IMC for nonlinear dynamic plants

  • Author

    Shafiq, Muhammed ; Butt, Naveed R.

  • Author_Institution
    Dept. of Syst. Eng., King Fahd Univ. of Pet. & Miner., Dhahran
  • Volume
    1
  • fYear
    2005
  • fDate
    19-22 Sept. 2005
  • Lastpage
    959
  • Abstract
    A novel technique, involving U-model based IMC (internal model control), is proposed for the adaptive control of nonlinear dynamic plants. The proposed scheme combines the robustness of the IMC and the ability of neural networks to identify arbitrary nonlinear functions, with the control-oriented nature of the U-model to achieve adaptive tracking of stable nonlinear plants. The proposed structure has a more general appeal than many other schemes involving polynomial NARMAX (nonlinear autoregressive moving average with exogenous inputs) model and the Hammerstein model, etc. Additionally, the control law is shown to be more simplistic in nature. The effectiveness of the proposed scheme is demonstrated with the help of simulations for the adaptive control of the Hammerstein model
  • Keywords
    autoregressive moving average processes; model reference adaptive control systems; neurocontrollers; nonlinear dynamical systems; Hammerstein model; U-model based adaptive internal model control; adaptive tracking; control law; neural network; nonlinear autoregressive moving average with exogenous inputs model; nonlinear dynamic plants; polynomial NARMAX; stable nonlinear plants; Adaptive control; Autoregressive processes; Control system synthesis; Minerals; Network synthesis; Neural networks; Nonlinear control systems; Petroleum; Polynomials; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies and Factory Automation, 2005. ETFA 2005. 10th IEEE Conference on
  • Conference_Location
    Catania
  • Print_ISBN
    0-7803-9401-1
  • Type

    conf

  • DOI
    10.1109/ETFA.2005.1612627
  • Filename
    1612627