Generalized likelihood ratio approach for fault detection in linear dynamic stochastic systems with unknown inputs

DOI10.1080/00207729608929330zbMath0869.93045OpenAlexW2071396201MaRDI QIDQ3124279

Mohamed Darouach, Leonhard Summerer, Jean-Yves Keller, Mohamed Boutayeb

Publication date: 8 September 1997

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

Full work available at URL: https://doi.org/10.1080/00207729608929330

zbMATH Keywords

Kalman filterfault detection and isolationdetectabilitygeneralized likelihood ratio testunknown inputs

Mathematics Subject Classification ID

Reliability, availability, maintenance, inspection in operations research (90B25) Estimation and detection in stochastic control theory (93E10)

Related Items

Unbiased information filtering for systems with missing measurement based on disturbance estimation, Threshold computation for fault detection in linear discrete-time Markov jump systems, Unbiased minimum-variance state estimation for linear systems with unknown input

Cites Work

• Process fault detection based on modeling and estimation methods - a survey
• Analytical redundancy and the design of robust failure detection systems
• Necessary and sufficient conditions for detectability of jumps in linear systems
• Observers for linear systems with unknown inputs