• DocumentCode
    2768683
  • Title

    Robust adaptive decoupling design for generalized predictive control with neural network

  • Author

    Qin, Xiao F. ; Zhu, Kuan Y. ; Chai, Tian Y.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
  • Volume
    3
  • fYear
    1996
  • fDate
    11-13 Dec 1996
  • Firstpage
    2426
  • Abstract
    A novel robust decoupling method with multivariable generalized predictive control (MGPC) for a class of nonlinear systems is presented in an adaptive version. System cross-coupling action and the nonlinear actors are identified online by a neural network, which is then compensated in the control algorithm using the feedforward technique to realize robust decoupling. The identified result is also taken as a modifying signal of the parameter estimate so that the equivalent model matches the real system well. Simulation results show the effectiveness of the proposed algorithm
  • Keywords
    adaptive control; compensation; control system synthesis; feedforward; multivariable control systems; neural nets; nonlinear control systems; parameter estimation; predictive control; robust control; feedforward technique; multivariable generalized predictive control; nonlinear actors; nonlinear systems; robust adaptive decoupling design; system cross-coupling action; Adaptive control; Control systems; Feedforward neural networks; Neural networks; Nonlinear control systems; Nonlinear systems; Predictive control; Programmable control; Robust control; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
  • Conference_Location
    Kobe
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-3590-2
  • Type

    conf

  • DOI
    10.1109/CDC.1996.573453
  • Filename
    573453