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Nonlinear system fault detection and isolation based on bootstrap particle filters

Qinghua Zhang 1 Fabien Campillo 2 Frédéric Cérou 2 François Le Gland 2
1 SOSSO2 - Applications and Tools of Automatic Control
Inria Paris-Rocquencourt
2 ASPI - Applications of interacting particle systems to statistics
UR1 - Université de Rennes 1, Inria Rennes – Bretagne Atlantique , CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : A particle filter based method for nonlinear system fault detection and isolation is proposed in this paper. It is applicable to quite general stochastic nonlinear dynamic systems in discrete time. The main result consists of a new particle filter algorithm, derived from the basic bootstrap particle filter, and capable of rejecting a subset of the faults possibly affecting the considered system. Fault isolation is then achieved by the evaluation of the estimated likelihoods related to the designed filters.
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Conference papers
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https://hal.inria.fr/hal-00943560
Contributor : Francois Le Gland <>
Submitted on : Friday, February 7, 2014 - 6:31:11 PM
Last modification on : Friday, May 25, 2018 - 12:02:04 PM

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UNIV-RENNES1 | CNRS | INRIA | INSMI | IRISA-D5 | UNIV-RENNES

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Qinghua Zhang, Fabien Campillo, Frédéric Cérou, François Le Gland. Nonlinear system fault detection and isolation based on bootstrap particle filters. Proceedings of the joint 44th Conference on Decision and Control and 8th European Control Conference, Seville 2005, IEEE--CSS, Dec 2005, Seville, Spain. pp.3821--3826, ⟨10.1109/CDC.2005.1582757⟩. ⟨hal-00943560⟩

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