• DocumentCode
    1006425
  • Title

    Identifying linear reduced-order models for systems with arbitrary initial conditions using Prony signal analysis

  • Author

    Pierre, D.A. ; Trudnowski, D.J. ; Hauer, J.F.

  • Author_Institution
    Dept. of Electr. Eng., Montana State Univ., Bozeman, MT, USA
  • Volume
    37
  • Issue
    6
  • fYear
    1992
  • fDate
    6/1/1992 12:00:00 AM
  • Firstpage
    831
  • Lastpage
    835
  • Abstract
    A method of identifying reduced-order linear models for systems operating in the neighborhood of an equilibrium point is presented. The method is based on Prony signal analysis, which has recently received considerable attention in the study of power system electromechanical oscillations. Prior to the application of the input test signal, the system can be in a transient state. The system input test signal is piecewise continuous and allows several Prony analyses to be performed during a transient, with each analysis conducted between input discontinuities. Results of these Prony analyses can be combined in various ways to obtain system eigenvalues, transfer-function residues, and initial condition residues. Two examples are given to illustrate the use of the method
  • Keywords
    eigenvalues and eigenfunctions; identification; multivariable systems; power system control; signal processing; transfer functions; transients; Prony signal analysis; eigenvalues; equilibrium point; identification; initial condition residues; multivariable systems; power system electromechanical oscillations; reduced-order linear models; transfer-function residues; transient; Eigenvalues and eigenfunctions; Performance analysis; Performance evaluation; Power system analysis computing; Power system modeling; Power system transients; Reduced order systems; Signal analysis; System testing; Transient analysis;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/9.256344
  • Filename
    256344