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dc.contributor.authorChung, IFen_US
dc.contributor.authorLin, CTen_US
dc.date.accessioned2014-12-08T15:26:51Z-
dc.date.available2014-12-08T15:26:51Z-
dc.date.issued2001en_US
dc.identifier.isbn0-7803-7078-3en_US
dc.identifier.urihttp://hdl.handle.net/11536/19107-
dc.description.abstractThis paper proposes a neuro-fuzzy combiner (NFC) with supervised learning capability for solving multiobjective control problems, The proposed NFC can combine n existing low-level controllers in a hierarchical way to form a multiobjective fuzzy controller. It is assumed that each low-level (fuzzy or nonfuzzy) controller has been well designed to serve a particular objective. The role of the NFC is to fuse the n actions decided by the n low-level controllers and determine a proper action acting on the environment (plant) at each time step. Hence, the NFC can combine low-level controllers and achieve multiple objectives (goals) at once. Here a NFC can be designed by proposed architecture and supervised learning scheme. Computer simulations have been conducted to illustrate the performance and applicability of the proposed architecture and learning scheme.en_US
dc.language.isoen_USen_US
dc.titleA neuro-fuzzy combiner for multiobjective controlen_US
dc.typeProceedings Paperen_US
dc.identifier.journalJOINT 9TH IFSA WORLD CONGRESS AND 20TH NAFIPS INTERNATIONAL CONFERENCE, PROCEEDINGS, VOLS. 1-5en_US
dc.citation.spage1384en_US
dc.citation.epage1389en_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:000173245100244-
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