• DocumentCode
    646482
  • Title

    Fault detection with unscented Kalman filter applied to nonlinear differential-algebraic systems

  • Author

    Alkov, Ilja ; Weidemann, Dirk

  • Author_Institution
    Dept. of Eng. Sci. & Math., Univ. of Appl. Sci. Bielefeld, Bielefeld, Germany
  • fYear
    2013
  • fDate
    26-29 Aug. 2013
  • Firstpage
    166
  • Lastpage
    171
  • Abstract
    This paper contemplates the unscented Kalman filter (UKF) algorithm for nonlinear semi-explicit index 1 differential-algebraic equation (DAE) systems. Incipient, the formulation of the UKF algorithm proposed by Mandela et al. in [1] concerning this system class is outlined and an revised formulation for the unscented Kalman filter for nonlinear semi-explicit index 1 differential-algebraic equation systems is described. Further, a simple and robust residual definition based on the state estimation with the introduced UKF is given aiming at the fault detection. Finally, simulation results illustrate the efficiency of the proposed fault detection approach applied to a hydraulic system.
  • Keywords
    Kalman filters; differential algebraic equations; nonlinear differential equations; DAE system; UKF algorithm; fault detection; hydraulic system; nonlinear differential-algebraic equation system; nonlinear semiexplicit index; residual definition; state estimation; unscented Kalman filter; Equations; Fault detection; Indexes; Kalman filters; Mathematical model; Object oriented modeling; State estimation; DAE; UKF; fault detection; nonlinear differential-algebraic systems; unscented Kalman filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Methods and Models in Automation and Robotics (MMAR), 2013 18th International Conference on
  • Conference_Location
    Miedzyzdroje
  • Print_ISBN
    978-1-4673-5506-3
  • Type

    conf

  • DOI
    10.1109/MMAR.2013.6669900
  • Filename
    6669900