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Article: Neurofuzzy network based adaptive integral control

TitleNeurofuzzy network based adaptive integral control
Authors
Liu, XJLaraRosano, FChan, CW
KeywordsNeurofuzzy networks
Nonlinear controller
Offset
Self-tuning control
Issue Date2003
PublisherACTA Press.
Citation
Control And Intelligent Systems, 2003, v. 31 n. 3, p. 173-180 How to Cite?
AbstractA self-tuning integral controller with offset removing ability using neurofuzzy methodology is derived for nonlinear control purpose. Controller Auto-Regressive Integrated Moving Average (CARIMA) model is used, and the control law produces integral control terms in a natural way. Neurofuzzy networks are chosen to implement the direct self-tuning nonlinear control. The performance of the self-tuning neurofuzzy controller is illustrated in detail by simulation examples involving both linear and nonlinear systems.
Persistent Identifierhttp://hdl.handle.net/10722/76097
ISSN
1480-1752
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorLiu, XJen_HK
dc.contributor.authorLaraRosano, Fen_HK
dc.contributor.authorChan, CWen_HK
dc.date.accessioned2010-09-06T07:17:37Z-
dc.date.available2010-09-06T07:17:37Z-
dc.date.issued2003en_HK
dc.identifier.citationControl And Intelligent Systems, 2003, v. 31 n. 3, p. 173-180en_HK
dc.identifier.issn1480-1752en_HK
dc.identifier.urihttp://hdl.handle.net/10722/76097-
dc.description.abstractA self-tuning integral controller with offset removing ability using neurofuzzy methodology is derived for nonlinear control purpose. Controller Auto-Regressive Integrated Moving Average (CARIMA) model is used, and the control law produces integral control terms in a natural way. Neurofuzzy networks are chosen to implement the direct self-tuning nonlinear control. The performance of the self-tuning neurofuzzy controller is illustrated in detail by simulation examples involving both linear and nonlinear systems.en_HK
dc.languageengen_HK
dc.publisherACTA Press.en_HK
dc.relation.ispartofControl and Intelligent Systemsen_HK
dc.subjectNeurofuzzy networksen_HK
dc.subjectNonlinear controlleren_HK
dc.subjectOffseten_HK
dc.subjectSelf-tuning controlen_HK
dc.titleNeurofuzzy network based adaptive integral controlen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1480-1752&volume=31&issue=3&spage=173&epage=180&date=2003&atitle=Neurofuzzy+network+based+adaptive+integral+controlen_HK
dc.identifier.emailChan, CW: mechan@hkucc.hku.hken_HK
dc.identifier.authorityChan, CW=rp00088en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0042931063en_HK
dc.identifier.hkuros79472en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0042931063&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume31en_HK
dc.identifier.issue3en_HK
dc.identifier.spage173en_HK
dc.identifier.epage180en_HK
dc.publisher.placeCanadaen_HK
dc.identifier.scopusauthoridLiu, XJ=37045874400en_HK
dc.identifier.scopusauthoridLaraRosano, F=6602865610en_HK
dc.identifier.scopusauthoridChan, CW=7404814060en_HK
dc.identifier.issnl1480-1752-

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