On the choice of importance distributions for unconstrained and constrained state estimation using particle filter
DSpace at IIT Bombay
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Title |
On the choice of importance distributions for unconstrained and constrained state estimation using particle filter
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Creator |
PRAKASH, J
PATWARDHAN, SC SHAH, SL |
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Subject |
ENSEMBLE KALMAN FILTER
BAYESIAN-ESTIMATION DATA RECONCILIATION SYSTEMS APPROXIMATIONS Nonlinear observers Particle filters Constrained state estimation Importance sampling Truncated distributions and unscented particle filter |
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Description |
Recursive state estimation of constrained nonlinear dynamical system has attracted the attention of many researchers in recent years. For nonlinear/non-Gaussian state estimation problems, particle filters have been widely used (Arulampalam et al. [1]). As pointed out by Daum [2], particle filters require a proposal distribution and the choice of proposal distribution is the key design issue. In this paper, a novel approach for generating the proposal distribution based on a constrained Extended Kalman filter (C-EKF), Constrained Unscented Kalman filter (C-UKF) and constrained Ensemble Kalman filter (C-EnkF) has been proposed. The efficacy of the proposed state estimation algorithms using a particle filter is illustrated via a successful implementation on a simulated gas-phase reactor, involving constraints on estimated state variables and another example problem, which involves constraints on the process noise (Rao et al. [10]). We also propose a state estimation scheme for estimating state variables in an autonomous hybrid system using particle filter with Unscented Kalman filter as a proposal and unconstrained Ensemble Kalman filter (EnKF) as a proposal. The efficacy of the proposed state estimation scheme for an autonomous hybrid system is demonstrated by conducting simulation studies on a three-tank hybrid system. The simulation studies underline the crucial role played by the choice of proposal distribution in formulation of particle filters. (C) 2010 Elsevier Ltd. All rights reserved.
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Publisher |
ELSEVIER SCI LTD
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Date |
2012-06-26T07:30:07Z
2012-06-26T07:30:07Z 2011 |
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Type |
Article
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Identifier |
JOURNAL OF PROCESS CONTROL,21(1)3-16
0959-1524 http://dx.doi.org/10.1016/j.jprocont.2010.08.001 http://dspace.library.iitb.ac.in/jspui/handle/100/14139 |
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Language |
English
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