• DocumentCode
    3244283
  • Title

    Identifiability and well-posedness in nonlinear system I/O modeling

  • Author

    Pearson, A.E.

  • Author_Institution
    Div. of Eng., Brown Univ., Providence, RI, USA
  • fYear
    1989
  • fDate
    13-15 Dec 1989
  • Firstpage
    624
  • Abstract
    If a specified set of parameterized nonlinear state differential equations possesses an equivalent input-output differential operator model, then the latter model has the potential for deciding the issue of the identifiability property of the former model in a straightforward manner. This property is discussed in relation to the property of well-posedness for the least-squares parameter identification of a class of input-output models that are separable in the parameters
  • Keywords
    differential equations; least squares approximations; nonlinear systems; parameter estimation; I/O modeling; identifiability; input-output differential operator model; least-squares parameter identification; nonlinear system; parameter estimation; parameterized nonlinear state differential equations; well-posedness; Differential equations; Least squares approximation; Least squares methods; Nonlinear systems; Parameter estimation; Phasor measurement units; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
  • Conference_Location
    Tampa, FL
  • Type

    conf

  • DOI
    10.1109/CDC.1989.70192
  • Filename
    70192