• DocumentCode
    3168092
  • Title

    Robust Fault Detection and Diagnosis for a Multiple Satellite Formation Flying System Using Second Order Sliding Mode and Wavelet Networks

  • Author

    Wu, Qing ; Saif, Mehrdad

  • Author_Institution
    Simon Fraser Univ., Vancouver
  • fYear
    2007
  • fDate
    9-13 July 2007
  • Firstpage
    426
  • Lastpage
    431
  • Abstract
    This paper presents a robust fault detection and diagnosis (FDD) scheme for abrupt and incipient faults in a class of nonlinear dynamic systems. A nonlinear observer which synthesizes second order sliding mode techniques and wavelet networks is proposed for online monitoring. The second order sliding mode is designed to eliminate the effect of system uncertainties on the state observation. Moreover, a bank of wavelet networks is constructed to isolate and estimate faults. Theoretically, the convergence of the state estimation using the second order sliding mode is analyzed. An adaptive algorithm is adopted to update the parameters of the wavelet networks, and its convergence is investigated as well. Finally, this robust FDD scheme is applied to a multiple satellite formation flying system, and simulation results illustrate its effectiveness.
  • Keywords
    artificial satellites; fault diagnosis; nonlinear dynamical systems; state estimation; variable structure systems; wavelet transforms; fault diagnosis; multiple satellite formation flying system; nonlinear dynamic systems; online monitoring; robust fault detection; second order sliding mode networks; state estimation; wavelet networks; Convergence; Fault detection; Fault diagnosis; Monitoring; Network synthesis; Nonlinear dynamical systems; Observers; Robustness; Satellites; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2007. ACC '07
  • Conference_Location
    New York, NY
  • ISSN
    0743-1619
  • Print_ISBN
    1-4244-0988-8
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2007.4282680
  • Filename
    4282680