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Intelligent backstepping control for chaotic systems using self-growing fuzzy neural network

dc.citation.epage308en_US
dc.citation.spage299en_US
dc.citation.volume344en_US
dc.contributor.authorLin, Chih-Minen_US
dc.contributor.authorHsu, Chun-Feien_US
dc.contributor.authorChung, I-Fangen_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.date.accessioned2014-12-08T15:17:50Z
dc.date.available2014-12-08T15:17:50Z
dc.date.issued2006en_US
dc.description.abstractThis paper proposes an intelligent backstepping control (IBC) for the chaotic systems. The IBC system is comprised of a neural backstepping controller and a robust compensation controller. The neural backstepping controller containing a self-growing fuzzy neural network (SGFNN) identifier is the principal controller, and the robust compensation controller is designed to dispel the effect of minimum approximation error introduced by the SGFNN identifier. Finally, simulation results verify that the IBC system can achieve favorable tracking performance.en_US
dc.identifier.isbn3-540-37255-5en_US
dc.identifier.issn0170-8643en_US
dc.identifier.journalINTELLIGENT CONTROL AND AUTOMATIONen_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/12918
dc.identifier.wosnumberWOS:000240383400037
dc.language.isoen_USen_US
dc.titleIntelligent backstepping control for chaotic systems using self-growing fuzzy neural networken_US
dc.typeArticle; Proceedings Paperen_US

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