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dc.contributor.authorWang, WYen_US
dc.contributor.authorLeu, YGen_US
dc.contributor.authorLee, TTen_US
dc.date.accessioned2014-12-08T15:40:05Z-
dc.date.available2014-12-08T15:40:05Z-
dc.date.issued2003-12-01en_US
dc.identifier.issn0165-0114en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0165-0114(02)00519-5en_US
dc.identifier.urihttp://hdl.handle.net/11536/27370-
dc.description.abstractIn this paper, a direct adaptive fuzzy-neural output-feedback controller (DAFOC) for a class of uncertain nonlinear systems is developed under the constraint that only the system output is available for measurement. An output feedback control law and an update law are derived for on-line tuning the weighting factors of the DAFOC. By using strictly positive-real Lyapunov theory, the stability of the closed-loop system compensated by the DAFOC can be verified. Moreover, the proposed overall control scheme guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper. (C) 2002 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectfuzzy-neural controlen_US
dc.subjectdirect adaptive controlen_US
dc.subjectoutput feedback controlen_US
dc.subjectnonlinear systemsen_US
dc.titleOutput-feedback control of nonlinear systems using direct adaptive fuzzy-neural controlleren_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0165-0114(02)00519-5en_US
dc.identifier.journalFUZZY SETS AND SYSTEMSen_US
dc.citation.volume140en_US
dc.citation.issue2en_US
dc.citation.spage341en_US
dc.citation.epage358en_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:000186507900006-
dc.citation.woscount33-
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