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Article: Model-reference adaptive control based on neurofuzzy networks

TitleModel-reference adaptive control based on neurofuzzy networks
Authors
Issue Date2004
PublisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5326
Citation
Ieee Transactions On Systems, Man And Cybernetics Part C: Applications And Reviews, 2004, v. 34 n. 3, p. 302-309 How to Cite?
AbstractModel reference adaptive control (MRAC) is a popular approach to control linear systems, as it is relatively simple to implement. However, the performance of the linear MRAC deteriorates rapidly when the system becomes nonlinear. In this paper, a nonlinear MRAC based on neurofuzzy networks is derived. Neurofuzzy networks are chosen not only because they can approximate nonlinear functions with arbitrary accuracy, but also they are compact in their supports, and the weights of the network can be readily updated on-line. The implementation of the neurofuzzy network-based MRAC is discussed, and the local stability of the system controlled by the proposed controller is established. The performance of the neurofuzzy network-based MRAC is illustrated by examples involving both linear and nonlinear systems. © 2004 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/43059
ISSN
2014 Impact Factor: 2.171
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLiu, XJen_HK
dc.contributor.authorLaraRosano, Fen_HK
dc.contributor.authorChan, CWen_HK
dc.date.accessioned2007-03-23T04:37:51Z-
dc.date.available2007-03-23T04:37:51Z-
dc.date.issued2004en_HK
dc.identifier.citationIeee Transactions On Systems, Man And Cybernetics Part C: Applications And Reviews, 2004, v. 34 n. 3, p. 302-309en_HK
dc.identifier.issn1094-6977en_HK
dc.identifier.urihttp://hdl.handle.net/10722/43059-
dc.description.abstractModel reference adaptive control (MRAC) is a popular approach to control linear systems, as it is relatively simple to implement. However, the performance of the linear MRAC deteriorates rapidly when the system becomes nonlinear. In this paper, a nonlinear MRAC based on neurofuzzy networks is derived. Neurofuzzy networks are chosen not only because they can approximate nonlinear functions with arbitrary accuracy, but also they are compact in their supports, and the weights of the network can be readily updated on-line. The implementation of the neurofuzzy network-based MRAC is discussed, and the local stability of the system controlled by the proposed controller is established. The performance of the neurofuzzy network-based MRAC is illustrated by examples involving both linear and nonlinear systems. © 2004 IEEE.en_HK
dc.format.extent378648 bytes-
dc.format.extent25088 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/msword-
dc.languageengen_HK
dc.publisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5326en_HK
dc.relation.ispartofIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviewsen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.titleModel-reference adaptive control based on neurofuzzy networksen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1094-6977&volume=34&issue=3&spage=302&epage=309&date=2004&atitle=Model-reference+adaptive+control+based+on+neurofuzzy+networksen_HK
dc.identifier.emailChan, CW: mechan@hkucc.hku.hken_HK
dc.identifier.authorityChan, CW=rp00088en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TSMCC.2003.819702en_HK
dc.identifier.scopuseid_2-s2.0-3542995092en_HK
dc.identifier.hkuros89128-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-3542995092&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume34en_HK
dc.identifier.issue3en_HK
dc.identifier.spage302en_HK
dc.identifier.epage309en_HK
dc.identifier.isiWOS:000222721200007-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLiu, XJ=37045874400en_HK
dc.identifier.scopusauthoridLaraRosano, F=6602865610en_HK
dc.identifier.scopusauthoridChan, CW=7404814060en_HK

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