Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/11144/3428 |
Resumo: | This paper addresses the problem of fault detection for linear parameter-varying systems in the presence of measurement noise and exogenous disturbances. The applicability of current methods is limited in the sense that, to increase accuracy, the detection requires a large number of past measurements and the boundedness of the set-valued estimates is only guaranteed for stable systems. In order to widen the class of systems to be modeled and also to reduce the associated computational cost, the aforementioned issues must be addressed. A solution involving left-coprime factorization and deadbeat observers is proposed in order to reduce the required number of past measurements without compromising accuracy and allowing the design of Set-Valued Observers (SVOs) for fault detection of unstable systems by using the resulting stable subsystems of the coprime factorization. The algorithm is shown to produce bounded set-valued estimates and an example is provided. Performance is assessed through simulations, illustrating, in particular that small-magnitude faults (compared to exogenous disturbances) can be detected under mild assumptions. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approachFault DetectionLinear Parameter-VaryingCoprime FactorizationDeadbeat ObserversThis paper addresses the problem of fault detection for linear parameter-varying systems in the presence of measurement noise and exogenous disturbances. The applicability of current methods is limited in the sense that, to increase accuracy, the detection requires a large number of past measurements and the boundedness of the set-valued estimates is only guaranteed for stable systems. In order to widen the class of systems to be modeled and also to reduce the associated computational cost, the aforementioned issues must be addressed. A solution involving left-coprime factorization and deadbeat observers is proposed in order to reduce the required number of past measurements without compromising accuracy and allowing the design of Set-Valued Observers (SVOs) for fault detection of unstable systems by using the resulting stable subsystems of the coprime factorization. The algorithm is shown to produce bounded set-valued estimates and an example is provided. Performance is assessed through simulations, illustrating, in particular that small-magnitude faults (compared to exogenous disturbances) can be detected under mild assumptions.Elsevier2018-02-07T11:49:58Z2017-08-01T00:00:00Z2017-08info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/11144/3428eng0167-691110.1016/j.sysconle.2017.05.007Silvestre, DanielRosa, P.Hespanha, J.P.Silvestre, C.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-08-01T02:07:28Zoai:repositorio.ual.pt:11144/3428Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-08-01T02:07:28Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach |
title |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach |
spellingShingle |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach Silvestre, Daniel Fault Detection Linear Parameter-Varying Coprime Factorization Deadbeat Observers |
title_short |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach |
title_full |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach |
title_fullStr |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach |
title_full_unstemmed |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach |
title_sort |
Fault detection for LPV systems using Set-Valued Observers: A coprime factorization approach |
author |
Silvestre, Daniel |
author_facet |
Silvestre, Daniel Rosa, P. Hespanha, J.P. Silvestre, C. |
author_role |
author |
author2 |
Rosa, P. Hespanha, J.P. Silvestre, C. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Silvestre, Daniel Rosa, P. Hespanha, J.P. Silvestre, C. |
dc.subject.por.fl_str_mv |
Fault Detection Linear Parameter-Varying Coprime Factorization Deadbeat Observers |
topic |
Fault Detection Linear Parameter-Varying Coprime Factorization Deadbeat Observers |
description |
This paper addresses the problem of fault detection for linear parameter-varying systems in the presence of measurement noise and exogenous disturbances. The applicability of current methods is limited in the sense that, to increase accuracy, the detection requires a large number of past measurements and the boundedness of the set-valued estimates is only guaranteed for stable systems. In order to widen the class of systems to be modeled and also to reduce the associated computational cost, the aforementioned issues must be addressed. A solution involving left-coprime factorization and deadbeat observers is proposed in order to reduce the required number of past measurements without compromising accuracy and allowing the design of Set-Valued Observers (SVOs) for fault detection of unstable systems by using the resulting stable subsystems of the coprime factorization. The algorithm is shown to produce bounded set-valued estimates and an example is provided. Performance is assessed through simulations, illustrating, in particular that small-magnitude faults (compared to exogenous disturbances) can be detected under mild assumptions. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-08-01T00:00:00Z 2017-08 2018-02-07T11:49:58Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/11144/3428 |
url |
http://hdl.handle.net/11144/3428 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0167-6911 10.1016/j.sysconle.2017.05.007 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
_version_ |
1817546653508304896 |