Estimation of parameters in a linear state space model using a Rao-Blackwellised particle filter
Estimation of parameters in a linear state space model using a Rao-Blackwellised particle filter
- Author(s): P. Li ; R. Goodall ; V. Kadirkamanathan
- DOI: 10.1049/ip-cta:20041008
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- Author(s): P. Li 1 ; R. Goodall 1 ; V. Kadirkamanathan 2
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View affiliations
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Affiliations:
1: Department of Electronic and Electrical Engineering, Loughborough University, Loughborough, UK
2: Department of Automatic Control & Systems Engineering, University of Sheffield, Sheffield, UK
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Affiliations:
1: Department of Electronic and Electrical Engineering, Loughborough University, Loughborough, UK
- Source:
Volume 151, Issue 6,
November 2004,
p.
727 – 738
DOI: 10.1049/ip-cta:20041008 , Print ISSN 1350-2379, Online ISSN 1359-7035
A Rao-Blackwellised particle filter is used in the estimation of the parameters of a linear stochastic state space model. The proposed method combines the particle filtering technique with a Kalman filter using marginalisation so as to make full use of the analytically tractable structure of the model. Simulation studies are performed on a simple illustrative example and the results demonstrate the effectiveness of the proposed method in comparison with the conventional extended-Kalman-filler-based method. The proposed method is then applied in the estimation of the parameters in a railway vehicle dynamic model for condition monitoring and the desired results have been obtained.
Inspec keywords: stochastic systems; parameter estimation; Kalman filters; state-space methods
Other keywords:
Subjects: Control system analysis and synthesis methods; Simulation, modelling and identification; Time-varying control systems
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