Robust fault detection based on adaptive threshold generation using interval LPV observers

In this paper, robust fault detection based on adaptive threshold generation of a non-linear system described by means of a linear parameter-varying (LPV) model is addressed. Adaptive threshold is generated using an interval LPV observer that generates a band of predicted outputs taking into account...

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Autores: Montes de Oca, Saúl, Puig Cayuela, Vicenç|||0000-0002-6364-6429, Blesa Izquierdo, Joaquim|||0000-0002-5626-3753
Tipo de recurso: artículo
Fecha de publicación:2012
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/15909
Acceso en línea:https://hdl.handle.net/2117/15909
https://dx.doi.org/10.1002/acs.1263
Access Level:acceso abierto
Palabra clave:Nonlinear control theory
Linear parameter-varying
Lnterval LPV observer
Linear matrix inequalities
Zonotopes
Minimum detectable fault
Control no lineal, Teoria
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
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oai_identifier_str oai:upcommons.upc.edu:2117/15909
network_acronym_str ES
network_name_str España
repository_id_str
spelling Robust fault detection based on adaptive threshold generation using interval LPV observersMontes de Oca, SaúlPuig Cayuela, Vicenç|||0000-0002-6364-6429Blesa Izquierdo, Joaquim|||0000-0002-5626-3753Nonlinear control theoryLinear parameter-varyingLnterval LPV observerLinear matrix inequalitiesZonotopesMinimum detectable faultControl no lineal, TeoriaÀrees temàtiques de la UPC::Informàtica::Automàtica i controlIn this paper, robust fault detection based on adaptive threshold generation of a non-linear system described by means of a linear parameter-varying (LPV) model is addressed. Adaptive threshold is generated using an interval LPV observer that generates a band of predicted outputs taking into account the parameter uncertainties bounded using intervals. An algorithm that propagates the uncertainty based on zonotopes is proposed. The design procedure of this interval LPV observer is implemented via pole placement using linear matrix inequalities. Finally, the minimum detectable fault is characterized using fault sensitivity analysis and residual uncertainty bounds. Two examples, one based on a quadruple-tank system and another based on a two-degree of freedom helicopter, are used to assess the validity of the proposed fault detection approach.20122012-01-0120122012-05-23journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/15909https://dx.doi.org/10.1002/acs.1263reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/159092026-05-27T15:37:01Z
dc.title.none.fl_str_mv Robust fault detection based on adaptive threshold generation using interval LPV observers
title Robust fault detection based on adaptive threshold generation using interval LPV observers
spellingShingle Robust fault detection based on adaptive threshold generation using interval LPV observers
Montes de Oca, Saúl
Nonlinear control theory
Linear parameter-varying
Lnterval LPV observer
Linear matrix inequalities
Zonotopes
Minimum detectable fault
Control no lineal, Teoria
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
title_short Robust fault detection based on adaptive threshold generation using interval LPV observers
title_full Robust fault detection based on adaptive threshold generation using interval LPV observers
title_fullStr Robust fault detection based on adaptive threshold generation using interval LPV observers
title_full_unstemmed Robust fault detection based on adaptive threshold generation using interval LPV observers
title_sort Robust fault detection based on adaptive threshold generation using interval LPV observers
dc.creator.none.fl_str_mv Montes de Oca, Saúl
Puig Cayuela, Vicenç|||0000-0002-6364-6429
Blesa Izquierdo, Joaquim|||0000-0002-5626-3753
author Montes de Oca, Saúl
author_facet Montes de Oca, Saúl
Puig Cayuela, Vicenç|||0000-0002-6364-6429
Blesa Izquierdo, Joaquim|||0000-0002-5626-3753
author_role author
author2 Puig Cayuela, Vicenç|||0000-0002-6364-6429
Blesa Izquierdo, Joaquim|||0000-0002-5626-3753
author2_role author
author
dc.subject.none.fl_str_mv Nonlinear control theory
Linear parameter-varying
Lnterval LPV observer
Linear matrix inequalities
Zonotopes
Minimum detectable fault
Control no lineal, Teoria
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
topic Nonlinear control theory
Linear parameter-varying
Lnterval LPV observer
Linear matrix inequalities
Zonotopes
Minimum detectable fault
Control no lineal, Teoria
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
description In this paper, robust fault detection based on adaptive threshold generation of a non-linear system described by means of a linear parameter-varying (LPV) model is addressed. Adaptive threshold is generated using an interval LPV observer that generates a band of predicted outputs taking into account the parameter uncertainties bounded using intervals. An algorithm that propagates the uncertainty based on zonotopes is proposed. The design procedure of this interval LPV observer is implemented via pole placement using linear matrix inequalities. Finally, the minimum detectable fault is characterized using fault sensitivity analysis and residual uncertainty bounds. Two examples, one based on a quadruple-tank system and another based on a two-degree of freedom helicopter, are used to assess the validity of the proposed fault detection approach.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-01-01
2012
2012-05-23
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/15909
https://dx.doi.org/10.1002/acs.1263
url https://hdl.handle.net/2117/15909
https://dx.doi.org/10.1002/acs.1263
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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