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
Link To Document :
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