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dc.contributor.authorXu, Feng
dc.contributor.authorTan, Junbo
dc.contributor.authorWang, Xueqian
dc.contributor.authorPuig Cayuela, Vicenç
dc.contributor.authorLiang, Bin
dc.contributor.authorYuan, Bo
dc.contributor.authorLiu, Houde
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2018-03-21T07:44:27Z
dc.date.available2018-11-13T01:30:40Z
dc.date.issued2017-02-16
dc.identifier.citationXu, F., Tan, J., Wang, X., Puig, V., Liang, B., Yuan, B., Liu, H. Generalized set-theoretic unknown input observer for LPV systems with application to state estimation and robust fault detection. "International journal of robust and nonlinear control", 16 Febrer 2017, vol. 27, núm. 17, p. 3812-3832.
dc.identifier.issn1049-8923
dc.identifier.urihttp://hdl.handle.net/2117/115495
dc.descriptionThis is the pre-peer reviewed version of the following article: [Xu, F., Tan, J., Wang, X., Puig, V., Liang, B., Yuan, B., and Liu, H. (2017) Generalized set-theoretic unknown input observer for LPV systems with application to state estimation and robust fault detection. Int. J. Robust. Nonlinear Control, 27: 3812–3832.], which has been published in final form at doi: 10.1002/rnc.3773. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."
dc.description.abstractThis paper proposes to design an unknown input observer (UIO) for the linear-parameter-varying (LPV) system on the basis of the set theory, which is named as the set-theoretic UIO (SUIO). The advantage of the SUIO consists in that it combines active and passive approaches to obtain robustness in state estimation (SE) and fault detection (FD). The active approach is based on the use of UIO to decouple unknown inputs, while the passive approach is based on the set theory to bound uncertain factors that cannot be actively decoupled. As a result, the effect of both unknown inputs (process disturbances, modeling errors, etc.) and measurement noises can be appropriately handled in the residual signals compared with the standard UIO-based SE and FD approaches. The design of SUIO can overcome the limitations of the traditional UIO design conditions, which can significantly broaden the application of the UIO-based SE and FD theory. Moreover, this paper proposes a generalized framework that can provide more flexibility in the design of SUIO guaranteeing their stability by means of a group of matrix inequalities. Because the LPV system uses a collection of online obtainable scheduling variables to embed nonlinearities, the design of SUIO for the LPV system can be used to address the SE and FD problems of nonlinear systems. At the end of this paper, two case studies are used to illustrate the effectiveness of the proposed approach. Copyright © 2017 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 tolerance (Engineering)
dc.subject.otherFault detection
dc.subject.otherstate estimation
dc.subject.otherunknown input observer
dc.subject.otherset theory
dc.subject.otherLPV system
dc.titleGeneralized set-theoretic unknown input observer for LPV systems with application to state estimation and robust fault detection
dc.typeArticle
dc.subject.lemacControl automàtic
dc.subject.lemacTolerància als errors (Enginyeria)
dc.contributor.groupUniversitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
dc.identifier.doi10.1002/rnc.3773
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://onlinelibrary.wiley.com/doi/abs/10.1002/rnc.3773
dc.rights.accessOpen Access
drac.iddocument19770847
dc.description.versionPostprint (author's final draft)
upcommons.citation.authorXu, F., Tan, J., Wang, X., Puig, V., Liang, B., Yuan, B., Liu, H.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameInternational journal of robust and nonlinear control
upcommons.citation.volume27
upcommons.citation.number17
upcommons.citation.startingPage3812
upcommons.citation.endingPage3832


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