• DocumentCode
    1310389
  • Title

    Neural-net-based direct adaptive control for a class of nonlinear plants

  • Author

    Ahmed, M.S.

  • Author_Institution
    E/E Eng., DaimlerCrysler Corp., Auburn Hills, MI, USA
  • Volume
    45
  • Issue
    1
  • fYear
    2000
  • fDate
    1/1/2000 12:00:00 AM
  • Firstpage
    119
  • Lastpage
    124
  • Abstract
    A direct adaptive control algorithm is presented for a class of nonlinear plants. No restriction has been imposed on the plant structure. The only condition the plant must satisfy is that the instantaneous input-output gain be positive. An artificial neural network (ANN)-based nonlinear controller structure has been employed. In line with the gain scheduling principle, however, the controller also has a pseudolinear time-varying structure with the parameters being the functions of the operating point. Simulation studies are also presented to validate the theoretical findings
  • Keywords
    adaptive control; controllers; neural nets; nonlinear control systems; direct adaptive control algorithm; instantaneous input-output gain; neural-net-based direct adaptive control; nonlinear controller structure; nonlinear plants; pseudolinear time-varying structure; simulation studies; Adaptive control; Artificial neural networks; Control systems; Convergence; Function approximation; Neural networks; Nonlinear control systems; Nonlinear systems; Robustness; Shape control;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/9.827367
  • Filename
    827367