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dc.contributor.authorMeseguer Amela, Jordi
dc.contributor.authorPuig Cayuela, Vicenç
dc.contributor.authorEscobet Canal, Teresa
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Minera, Industrial i TIC
dc.date.accessioned2018-04-04T10:03:39Z
dc.date.available2018-07-03T00:30:34Z
dc.date.issued2017-07-01
dc.identifier.citationMeseguer, J., Puig, V., Escobet, T. Approximating fault detection linear interval observers using -order interval predictors. "International journal of adaptive control and signal processing", 1 Juliol 2017, vol. 31, núm. 7, p. 1040-1060.
dc.identifier.issn0890-6327
dc.identifier.urihttp://hdl.handle.net/2117/115916
dc.description"This is the peer reviewed version of the following article:Meseguer, J., Puig, V., and Escobet, T. (2017) Approximating fault detection linear interval observers using ¿-order interval predictors. Int. J. Adapt. Control Signal Process., 31: 1040–1060., which has been published in final form at https://doi.org/10.1002/acs.2746. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."
dc.description.abstractInterval observers can be described by an autoregressive-moving-average model while ¿-order interval predictors by a moving-average model. Because an autoregressive-moving-average (ARMA) model can be approximated by a moving-average model, this allows establishing the equivalence between interval observers and interval predictors. This paper deals with the fault detection application and focuses on the equivalence between the ¿-orderintervalpredictorsand the interval observers from the point of view of the fault detection performance. The paper also proves that it is possible to obtain an equivalent ¿ - order interval predictor for a given interval observer with the same fault detection properties by the appropriate selection of the ¿ - order. A condition for selecting the minimal order that provides the ¿ - order interval predictor equivalent to a given interval observer is derived. Moreover, because the wrapping effect could be avoided by tuning properly the interval observer, we can find an equivalent ¿ - order interval predictor such that it also avoids the wrapping effect. Finally, an example based on an industrial servo actuator will be used to illustrate the derived results. Copyright © 2016 John Wiley & Sons, Ltd.
dc.format.extent21 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshAutomatic control
dc.subject.lcshFault location (Engineering)
dc.subject.otherObservers
dc.subject.otherpredictors
dc.subject.otherfault detection
dc.subject.otherintervals
dc.titleApproximating fault detection linear interval observers using -order interval predictors
dc.typeArticle
dc.subject.lemacControl automàtic
dc.subject.lemacErrors de sistemes (Enginyeria)
dc.subject.lemacControl de processos
dc.contributor.groupUniversitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
dc.identifier.doi10.1002/acs.2746
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://onlinelibrary.wiley.com/doi/10.1002/acs.2746/abstract;jsessionid=26BFDD76B6299F7B99DCAEA2D9BEC705.f03t02
dc.rights.accessOpen Access
drac.iddocument21185092
dc.description.versionPostprint (author's final draft)
upcommons.citation.authorMeseguer, J., Puig, V., Escobet, T.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameInternational journal of adaptive control and signal processing
upcommons.citation.volume31
upcommons.citation.number7
upcommons.citation.startingPage1040
upcommons.citation.endingPage1060


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain