• DocumentCode
    490560
  • Title

    A New Method for Identifying Orders of Input-Output Models for Nonlinear Dynamic Systems

  • Author

    He, Xiangdong ; Asada, Haruhiko

  • Author_Institution
    Center for Information-Driven Mechanical Systems, Department of Mechanical Engineering, Massachusetts Institute of Technology
  • fYear
    1993
  • fDate
    2-4 June 1993
  • Firstpage
    2520
  • Lastpage
    2523
  • Abstract
    The paper proposes a new method for identifying orders of input-output models for unknown nonlinear dynamic systems. The approach is based on the continuity property of the nonlinear functions which represent input-output models of continuous dynamic systems. The approach does not depend on any nonlinear function approximation methods and solely depends on the system´s input-output data measured in experiments. By evaluating the modification of an index which is defined as Lipschitz number with the successive modification of model orders, the appropriate model orders can be determined simply and reliably. Theoretical background of the present approach is discussed. Several examples from chaotic dynamic systems, nonlinear plant models are presented to demonstrate the effectiveness of the present method.
  • Keywords
    Approximation methods; Artificial neural networks; Function approximation; Helium; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Polynomials; Predictive models; Radial basis function networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 1993
  • Conference_Location
    San Francisco, CA, USA
  • Print_ISBN
    0-7803-0860-3
  • Type

    conf

  • Filename
    4793346