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dc.contributor.authorHsu, Chun-Feien_US
dc.contributor.authorLee, Tsu-Tianen_US
dc.contributor.authorWen, Yao-Weien_US
dc.contributor.authorDing, Fu-Shanen_US
dc.date.accessioned2014-12-08T15:24:46Z-
dc.date.available2014-12-08T15:24:46Z-
dc.date.issued2006en_US
dc.identifier.isbn978-0-7803-9488-9en_US
dc.identifier.issn1098-7584en_US
dc.identifier.urihttp://hdl.handle.net/11536/17212-
dc.description.abstractFor many years, the control approaches for the dc-dc power converters are limited to PI controller structures. However, it gives the overshoot in output voltage as the rise time of response is reduced. To tackle this problem, an adaptive recurrent fuzzy neural network (ARFNN) control system is developed in this paper. The on-line adaptive laws of the ARFNN control scheme are derived based on the Lyapunov stability theorem, so that the stability of the system can be guaranteed. Experimental results show that the proposed ARFNN control scheme can achieve good regulation performances.en_US
dc.language.isoen_USen_US
dc.titleIntelligent control for DC-DC power converter with recurrent fuzzy neural network approachen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2006 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5en_US
dc.citation.spage457en_US
dc.citation.epage462en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000244063600066-
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