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dc.contributor.authorSala, Antonio
dc.contributor.authorAriño Latorre, Carlos Vicente
dc.date.accessioned2014-06-12T11:54:56Z
dc.date.available2014-06-12T11:54:56Z
dc.date.issued2009-12
dc.identifier.issn1063-6706
dc.identifier.urihttp://hdl.handle.net/10234/94702
dc.description.abstractClassical Takagi-Sugeno (T-S) fuzzy models are formed by convex combinations of linear consequent local models. Such fuzzy models can be obtained from nonlinear first-principle equations by the well-known sector-nonlinearity modeling technique. This paper extends the sector-nonlinearity approach to the polynomial case. This way, generalized polynomial fuzzy models are obtained. The new class of models is polynomial, both in the membership functions and in the consequent models. Importantly, T-S models become a particular case of the proposed technique. Recent possibilities for stability analysis and controller synthesis are also discussed. A set of examples shows that polynomial modeling is able to reduce conservativeness with respect to standard T-S approaches as the degrees of the involved polynomials increase.ca_CA
dc.format.extent11 p.ca_CA
dc.language.isoengca_CA
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)ca_CA
dc.relation.isPartOfIEEE Transactions on Fuzzy Systems, 17, 6, p. 1284 - 1295ca_CA
dc.rights© 2009 IEEEca_CA
dc.subjectfuzzy controlca_CA
dc.subjectfuzzy modelingca_CA
dc.subjectpolynomial fuzzy systemsca_CA
dc.subjectrelaxed stability conditionsca_CA
dc.subjectsum of squares (SOS)ca_CA
dc.titlePolynomial Fuzzy Models for Nonlinear Control: A Taylor Series Approachca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1109/TFUZZ.2009.2029235
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccessca_CA
dc.relation.publisherVersionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5191124&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A5338640%29ca_CA


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