Fault detection and isolation in non-linear stochastic systems—A combined adaptive Monte Carlo filtering and likelihood ratio approach

DOI10.1080/00207170412331293311zbMath1071.93050OpenAlexW2007779284WikidataQ59265176 ScholiaQ59265176MaRDI QIDQ4652077

Ping Li, Visakan Kadirkamanathan

Publication date: 24 February 2005

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207170412331293311

zbMATH Keywords

predictionfault detection and isolationnonlinear stochastic systemslikelihood estimationMonte Carlo filter

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Filtering in stochastic control theory (93E11) Monte Carlo methods (65C05) Reliability, availability, maintenance, inspection in operations research (90B25) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)

Related Items (4)

Computational system identification for Bayesian NARMAX modelling ⋮ Hybrid fault diagnosis of nonlinear systems using neural parameter estimators ⋮ Diagnosis of unknown parametric faults in non-linear stochastic dynamical systems ⋮ Multi-faults detection and estimation for nonlinear stochastic system based on particle filter and hypothesis test

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