Well-conditioned robust observer for detection of faulty systems components
Autor(a) principal: | |
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Data de Publicação: | 1997 |
Outros Autores: | |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | https://www.sem.org/Proceedings/ConferencePapers-Paper.cfm?ConfPapersPaperID=39220 http://hdl.handle.net/11449/65324 |
Resumo: | A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures. |
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Repositório Institucional da UNESP |
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2946 |
spelling |
Well-conditioned robust observer for detection of faulty systems componentsDetectorsFailure analysisRobustness (control systems)SensorsObserversControl system synthesisA new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.UNESP, Ilha SolteiraUNESP, Ilha SolteiraUniversidade Estadual Paulista (Unesp)Melo, G. P. [UNESP]Pederiva, R.2014-05-27T11:18:19Z2014-05-27T11:18:19Z1997-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1899-1903https://www.sem.org/Proceedings/ConferencePapers-Paper.cfm?ConfPapersPaperID=39220Proceedings of the International Modal Analysis Conference - IMAC, v. 2, p. 1899-1903.1046-6770http://hdl.handle.net/11449/653242-s2.0-00313359857921787048065279Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the International Modal Analysis Conference - IMACinfo:eu-repo/semantics/openAccess2024-07-04T20:06:43Zoai:repositorio.unesp.br:11449/65324Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:45:02.772568Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Well-conditioned robust observer for detection of faulty systems components |
title |
Well-conditioned robust observer for detection of faulty systems components |
spellingShingle |
Well-conditioned robust observer for detection of faulty systems components Melo, G. P. [UNESP] Detectors Failure analysis Robustness (control systems) Sensors Observers Control system synthesis |
title_short |
Well-conditioned robust observer for detection of faulty systems components |
title_full |
Well-conditioned robust observer for detection of faulty systems components |
title_fullStr |
Well-conditioned robust observer for detection of faulty systems components |
title_full_unstemmed |
Well-conditioned robust observer for detection of faulty systems components |
title_sort |
Well-conditioned robust observer for detection of faulty systems components |
author |
Melo, G. P. [UNESP] |
author_facet |
Melo, G. P. [UNESP] Pederiva, R. |
author_role |
author |
author2 |
Pederiva, R. |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Melo, G. P. [UNESP] Pederiva, R. |
dc.subject.por.fl_str_mv |
Detectors Failure analysis Robustness (control systems) Sensors Observers Control system synthesis |
topic |
Detectors Failure analysis Robustness (control systems) Sensors Observers Control system synthesis |
description |
A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures. |
publishDate |
1997 |
dc.date.none.fl_str_mv |
1997-12-01 2014-05-27T11:18:19Z 2014-05-27T11:18:19Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.sem.org/Proceedings/ConferencePapers-Paper.cfm?ConfPapersPaperID=39220 Proceedings of the International Modal Analysis Conference - IMAC, v. 2, p. 1899-1903. 1046-6770 http://hdl.handle.net/11449/65324 2-s2.0-0031335985 7921787048065279 |
url |
https://www.sem.org/Proceedings/ConferencePapers-Paper.cfm?ConfPapersPaperID=39220 http://hdl.handle.net/11449/65324 |
identifier_str_mv |
Proceedings of the International Modal Analysis Conference - IMAC, v. 2, p. 1899-1903. 1046-6770 2-s2.0-0031335985 7921787048065279 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of the International Modal Analysis Conference - IMAC |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1899-1903 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129548154306560 |