• DocumentCode
    2857784
  • Title

    Fault detection and diagnosis of an electrohydrostatic actuator using a novel interacting multiple model approach

  • Author

    Gadsden, S.A. ; McCullough, K. ; Habibi, S.R.

  • Author_Institution
    Dept. of Mech. Eng., McMaster Univ., Hamilton, ON, Canada
  • fYear
    2011
  • fDate
    June 29 2011-July 1 2011
  • Firstpage
    1396
  • Lastpage
    1401
  • Abstract
    In this paper, a new type of interacting multiple model (IMM) is introduced for the purposes of fault detection and diagnosis. The standard IMM is combined with a relatively new filtering method referred to as the smooth variable structure filter (SVSΓ). The SVSF is a type of sliding mode estimator, formulated in a predictor-correct fashion. It keeps the estimated state close to the true trajectory, and creates a stable estimation process. The combined method, referred to as the SVSF-IMM, is applied to an electrohydrostatic actuator (EHA). The results of the experiment are compared with the common form of the IMM, which utilizes the popular Kalman filter (KΓ).
  • Keywords
    Kalman filters; electric actuators; fault diagnosis; hydrostatics; variable structure systems; Kalman filter; SVSF-IMM; electrohydrostatic actuator; fault detection; fault diagnosis; filtering method; interacting multiple model approach; predictor-correct fashion; sliding mode estimator; smooth variable structure filter; stable estimation process; standard IMM; Actuators; Estimation; Fault detection; Friction; Mathematical model; Probability; Valves;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2011
  • Conference_Location
    San Francisco, CA
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4577-0080-4
  • Type

    conf

  • DOI
    10.1109/ACC.2011.5991440
  • Filename
    5991440