Particle filtering-based fault detection in non-linear stochastic systems

DOI10.1080/00207720110102566zbMath1012.93064OpenAlexW2141026532WikidataQ59265189 ScholiaQ59265189MaRDI QIDQ4784565

Ping Li, Simon G. Fabri, Visakan Kadirkamanathan, M. H. Jaward

Publication date: 23 April 2003

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207720110102566

zbMATH Keywords

nonlinear stochastic systemslikelihood-based fault detectionparticle filtering fault detection

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Reliability, availability, maintenance, inspection in operations research (90B25) Nonlinear systems in control theory (93C10) Detection theory in information and communication theory (94A13)

Related Items (9)

Efficient estimation of hybrid systems with applications to tracking ⋮ Real-time model-based fault detection and isolation for ugvs ⋮ Integrity assurance of GNSS-based train integrated positioning system ⋮ Structure detection and parameter estimation for NARX models in a unified EM framework ⋮ Fault detection and isolation in non-linear stochastic systems—A combined adaptive Monte Carlo filtering and likelihood ratio approach ⋮ A Novel Fuzzy Approach for State Estimation of Nonlinear Hybrid Systems Using Particle Filtering Method ⋮ Particle filter with one-step randomly delayed measurements and unknown latency probability ⋮ A new conditional posterior Cramér-Rao lower bound for a class of nonlinear systems ⋮ Estimation of structural changes in nonlinear time series models by using particle filters and genetic programming

Cites Work

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• Non-linear adaptive fault detection filter
• Designing dynamic consistency relations for fault detection and isolation
• Monte Carlo techniques to estimate the conditional expectation in multi-stage non-linear filtering†
• Monte Carlo filters for non-linear state estimation

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