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Subspace-Based Takagi-Sugeno Modeling for Improved LMI Performance

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Subspace-Based Takagi-Sugeno Modeling for Improved LMI Performance

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dc.contributor.author Robles-Ruiz, Ruben es_ES
dc.contributor.author Sala, Antonio es_ES
dc.contributor.author Bernal Reza, Miguel Ángel es_ES
dc.contributor.author Gonzalez-German, Ivan Temoatzin es_ES
dc.date.accessioned 2020-07-17T03:31:52Z
dc.date.available 2020-07-17T03:31:52Z
dc.date.issued 2017-08 es_ES
dc.identifier.issn 1063-6706 es_ES
dc.identifier.uri http://hdl.handle.net/10251/148179
dc.description "© 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." es_ES
dc.description.abstract [EN] Given a nonlinear system, the sector-nonlinearity methodology provides a systematic way of transforming it in an equivalent Takagi-Sugeno (T-S) model. However, such transformation is not unique: conservatism of shape-independent performance conditions in the form of linear matrix inequalities results in some models yielding better results than others. This paper provides some guidelines on choosing a sector-nonlinearity T-S model, with provable optimality (in a particular sense) in the case of quadratic nonlinearities. The approach is based on Hessian and restrictions of a function onto a subspace. es_ES
dc.description.sponsorship This work was supported by the following institutions: Project Ciencia Basica SEP-CONACYT CB-168406, Project DPI2016-81002, (Spanish government, MINECO), Grant PROMETEOII/2013/004 (Generalitat Valenciana) and, the Scholarship GRISOLIA/2014/006. es_ES
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers es_ES
dc.relation.ispartof IEEE Transactions on Fuzzy Systems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Optimized production technology es_ES
dc.subject Analytical models es_ES
dc.subject Takagi-Sugeno model es_ES
dc.subject Symmetric matrices es_ES
dc.subject Eigenvalues and eigenfunctions es_ES
dc.subject Systematics es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title Subspace-Based Takagi-Sugeno Modeling for Improved LMI Performance es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/TFUZZ.2016.2574927 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//DPI2016-81002-R/ES/CONTROL AVANZADO Y APRENDIZAJE DE ROBOTS EN OPERACIONES DE TRANSPORTE/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CONACyT//CB-168406/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//GRISOLIA%2F2014%2F006/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//GRISOLIAP%2F2014%2F080/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2013%2F004/ES/DISEÑO DE SISTEMAS DE CONTROL MULTIVARIABLE (DISICOM)/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Robles-Ruiz, R.; Sala, A.; Bernal Reza, MÁ.; Gonzalez-German, IT. (2017). Subspace-Based Takagi-Sugeno Modeling for Improved LMI Performance. IEEE Transactions on Fuzzy Systems. 25(4):754-767. https://doi.org/10.1109/TFUZZ.2016.2574927 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1109/TFUZZ.2016.2574927 es_ES
dc.description.upvformatpinicio 754 es_ES
dc.description.upvformatpfin 767 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 25 es_ES
dc.description.issue 4 es_ES
dc.relation.pasarela S\343100 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Consejo Nacional de Ciencia y Tecnología, México es_ES


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