• DocumentCode
    2389874
  • Title

    Constrained state estimation using the ensemble Kalman filter

  • Author

    Prakash, J. ; Patwardhan, Sachin C. ; Shah, Sirish L.

  • Author_Institution
    Dept. of Instrum. Eng. MIT Campus, Anna Univ., Chennai
  • fYear
    2008
  • fDate
    11-13 June 2008
  • Firstpage
    3542
  • Lastpage
    3547
  • Abstract
    Recursive estimation of constrained nonlinear dynamical systems has attracted the attention of many researchers in recent years. In this work, we propose a constrained recursive formulation of the ensemble Kalman filter (CEnKF) that retains the advantages of unconstrained Ensemble Kalman Filter while systematically dealing with bounds on the estimated states. The efficacy of the proposed constrained state estimation algorithm using the EnKF is illustrated by application on a simulated gas-phase reactor problem.
  • Keywords
    Kalman filters; nonlinear dynamical systems; recursive estimation; state estimation; CEnKF; constrained state estimation; ensemble Kalman filter; gas-phase reactor problem; nonlinear dynamical systems; recursive estimation; Bayesian methods; Control systems; Filtering; Inductors; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Particle filters; Recursive estimation; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2008
  • Conference_Location
    Seattle, WA
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-2078-0
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2008.4587042
  • Filename
    4587042