• DocumentCode
    3170909
  • Title

    Sensor-to-sensor identification of Hammerstein systems

  • Author

    Aljanaideh, Khaled F. ; Ali, Ahmed Abdalla ; Holzel, M.S. ; Kukreja, S.L. ; Bernstein, D.S.

  • Author_Institution
    Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    2846
  • Lastpage
    2851
  • Abstract
    Traditional system identification uses measurements of the inputs, but when these measurements are not available, alternative methods, such as blind identification, output-only identification, or operational modal analysis, must be used. Yet another method is sensor-to-sensor identification (S2SID), which estimates pseudo transfer functions whose inputs are outputs of the original system. A special case of S2SID is transmissibility identification. Since S2SID depends on cancellation of the input, this approach does not extend to nonlinear systems. However, in the present paper we show that, for the case of a two-output Hammerstein system, the least-squares estimate of the PTF is consistent, that is, asymptotically correct, despite the presence of the nonlinearities.
  • Keywords
    control nonlinearities; identification; modal analysis; nonlinear control systems; transfer functions; Hammerstein system; blind identification; least-squares estimation; nonlinear system; nonlinearities; operational modal analysis; output-only identification; pseudo transfer function estimation; sensor-to-sensor identification; system identification; transmissibility identification; Aerodynamics; Finite impulse response filter; Least squares approximation; Markov processes; Noise; Random processes; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-2065-8
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2012.6426385
  • Filename
    6426385