DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zhang, HG | ko |
dc.contributor.author | Bien, Zeung nam | ko |
dc.date.accessioned | 2013-02-27T17:06:39Z | - |
dc.date.available | 2013-02-27T17:06:39Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2000-10 | - |
dc.identifier.citation | FUZZY SETS AND SYSTEMS, v.115, no.2, pp.191 - 204 | - |
dc.identifier.issn | 0165-0114 | - |
dc.identifier.uri | http://hdl.handle.net/10203/69747 | - |
dc.description.abstract | This paper presents a novel fuzzy basis function approach for adaptive control of multi-input and multi-output (MIMO) systems. In the method the nonlinear plant is first linearised and the fuzzy basis function vector is introduced to adaptively learn the upper bound of the system uncertainty vector, while its output is used as the parameter of the compensator in the sense that both the robustness and the asymptotic error convergence can be obtained for the closed loop nonlinear control system. (C) 2000 Elsevier Science B.V. All rights reserved. | - |
dc.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.subject | NEURAL NETWORKS | - |
dc.title | Adaptive fuzzy control of MIMO nonlinear systems | - |
dc.type | Article | - |
dc.identifier.wosid | 000088811500002 | - |
dc.identifier.scopusid | 2-s2.0-0034299696 | - |
dc.type.rims | ART | - |
dc.citation.volume | 115 | - |
dc.citation.issue | 2 | - |
dc.citation.beginningpage | 191 | - |
dc.citation.endingpage | 204 | - |
dc.citation.publicationname | FUZZY SETS AND SYSTEMS | - |
dc.contributor.localauthor | Bien, Zeung nam | - |
dc.contributor.nonIdAuthor | Zhang, HG | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | MIMO | - |
dc.subject.keywordAuthor | stability | - |
dc.subject.keywordAuthor | fuzzy basic function vector | - |
dc.subject.keywordAuthor | nonlinear system | - |
dc.subject.keywordPlus | NEURAL NETWORKS | - |
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