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Conference Paper: Sensor fault diagnosis for systems with unknown nonlinearity using neural network based nonlinear observers

TitleSensor fault diagnosis for systems with unknown nonlinearity using neural network based nonlinear observers
Authors
Issue Date1998
Citation
Iee Conference Publication, 1998 n. 455, p. 981-986 How to Cite?
AbstractA nonlinear observer for fault detection and isolation (FDI) of systems with unknown nonlinearity is presented. The nonlinear compensation term in the observer design is obtained by a 'deconvolution' method and a B-spline neural network. The problem with the use of one-step ahead prediction error of the observer in FDI is discussed, and an alternative approach based on multi-step ahead prediction is proposed. A nonlinear 'dedicated observer' scheme for the FDI using multiple measurements is also discussed.
Persistent Identifierhttp://hdl.handle.net/10722/100439
ISSN

 

DC FieldValueLanguage
dc.contributor.authorZhang, HYen_HK
dc.contributor.authorChan, CWen_HK
dc.contributor.authorCheung, KCen_HK
dc.contributor.authorJin, Hongen_HK
dc.date.accessioned2010-09-25T19:10:04Z-
dc.date.available2010-09-25T19:10:04Z-
dc.date.issued1998en_HK
dc.identifier.citationIee Conference Publication, 1998 n. 455, p. 981-986en_HK
dc.identifier.issn0537-9989en_HK
dc.identifier.urihttp://hdl.handle.net/10722/100439-
dc.description.abstractA nonlinear observer for fault detection and isolation (FDI) of systems with unknown nonlinearity is presented. The nonlinear compensation term in the observer design is obtained by a 'deconvolution' method and a B-spline neural network. The problem with the use of one-step ahead prediction error of the observer in FDI is discussed, and an alternative approach based on multi-step ahead prediction is proposed. A nonlinear 'dedicated observer' scheme for the FDI using multiple measurements is also discussed.en_HK
dc.languageengen_HK
dc.relation.ispartofIEE Conference Publicationen_HK
dc.titleSensor fault diagnosis for systems with unknown nonlinearity using neural network based nonlinear observersen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChan, CW: mechan@hkucc.hku.hken_HK
dc.identifier.emailCheung, KC: kccheung@hkucc.hku.hken_HK
dc.identifier.authorityChan, CW=rp00088en_HK
dc.identifier.authorityCheung, KC=rp01322en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0031994364en_HK
dc.identifier.hkuros41231en_HK
dc.identifier.issue455en_HK
dc.identifier.spage981en_HK
dc.identifier.epage986en_HK
dc.identifier.scopusauthoridZhang, HY=7409196387en_HK
dc.identifier.scopusauthoridChan, CW=7404814060en_HK
dc.identifier.scopusauthoridCheung, KC=7402406698en_HK
dc.identifier.scopusauthoridJin, Hong=34770583400en_HK

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