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dc.contributor.authorLi, Shih-Yuen_US
dc.contributor.authorTam, Lap-Mouen_US
dc.contributor.authorTsai, Shang-Enen_US
dc.contributor.authorGe, Zheng-Mingen_US
dc.date.accessioned2017-04-21T06:55:17Z-
dc.date.available2017-04-21T06:55:17Z-
dc.date.issued2016-10en_US
dc.identifier.issn2168-2267en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TCYB.2015.2473660en_US
dc.identifier.urihttp://hdl.handle.net/11536/134195-
dc.description.abstractGe and Li proposed an alternative strategy to model and synchronize two totally different nonlinear systems in the end of 2011, which provided a new version for fuzzy modeling and has been applied to several fields to simplify their modeling works and solve the mismatch problems [1]-[17]. However, the proposed model limits the number of nonlinear terms in each equation so that this model could not be used in all kinds of nonlinear dynamic systems. As a result, in this paper, a more efficient and comprehensive advanced-Ge-Li fuzzy model is given to further release the limitation and improve the effectiveness of the original one. The novel fuzzy model can be applied to all kinds of complex nonlinear systems-this is the universal strategy and only m x 2 fuzzy rules as well as two linear subsystems are needed to simulate nonlinear behaviors (m is the number of states in a nonlinear dynamic system), whatever the nonlinear terms are copious or complicated. Further, the fuzzy synchronization of two nonlinear dynamic systems with totally distinct structures can be achieved via only two sets of control gains designed through the novel fuzzy model as well as its corresponding fuzzy synchronization scheme. Two complicated dynamic systems are designed to be the illustrations, Mathieu-Van der pol system with uncertainties and Quantum-cellular neural networks nano system with uncertainties, to show the effectiveness and feasibility of the novel fuzzy model.en_US
dc.language.isoen_USen_US
dc.subjectComplicated nonlinear systemen_US
dc.subjectGe-Li fuzzy modelen_US
dc.subjectsynchronizations of systems with distinct structuresen_US
dc.titleNovel Fuzzy Modeling and Synchronization of Chaotic Systems With Multinonlinear Terms by Advanced Ge-Li Fuzzy Modelen_US
dc.identifier.doi10.1109/TCYB.2015.2473660en_US
dc.identifier.journalIEEE TRANSACTIONS ON CYBERNETICSen_US
dc.citation.volume46en_US
dc.citation.issue10en_US
dc.citation.spage2228en_US
dc.citation.epage2237en_US
dc.contributor.department機械工程學系zh_TW
dc.contributor.departmentDepartment of Mechanical Engineeringen_US
dc.identifier.wosnumberWOS:000384265600013en_US
Appears in Collections:Articles