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Conference Paper: Intelligent Variable Structure Control for Automated Guided Vehicle

TitleIntelligent Variable Structure Control for Automated Guided Vehicle
Authors
Issue Date2008
PublisherIEEE
Citation
2008 IEEE Congress on Evolutionary Computation, Hong Kong, 1-6 June 2008, p. 3968 - 3973 How to Cite?
AbstractAiming at Automated Guided Vehicle (AGV) dynamic model characteristics, a Variable Structure Control based on genetic algorithm (GA) and least square-support vector machine (LS-SVM) was designed. Parameters, predetermined by conventional reaching law, were regulated by LS-SVM online. It was shown that system shattering is eliminated. Simulation results indicated that this method possesses the advantages of higher precision, greater adaptability and robustness, as compared to the conventional Variable Structure Control methods. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/96955
ISBN
ISSN
2021 Impact Factor: 16.497
2020 SCImago Journal Rankings: 3.463
References

 

DC FieldValueLanguage
dc.contributor.authorJiao, Jen_HK
dc.contributor.authorChen, WWen_HK
dc.contributor.authorLeung, KSen_HK
dc.contributor.authorLi, SWen_HK
dc.contributor.authorWang, JXen_HK
dc.contributor.authorCheung, WKCen_HK
dc.contributor.authorLin, MCen_HK
dc.date.accessioned2010-09-25T16:51:08Z-
dc.date.available2010-09-25T16:51:08Z-
dc.date.issued2008en_HK
dc.identifier.citation2008 IEEE Congress on Evolutionary Computation, Hong Kong, 1-6 June 2008, p. 3968 - 3973-
dc.identifier.isbn978-1-4244-1822-0-
dc.identifier.issn1089-778X-
dc.identifier.urihttp://hdl.handle.net/10722/96955-
dc.description.abstractAiming at Automated Guided Vehicle (AGV) dynamic model characteristics, a Variable Structure Control based on genetic algorithm (GA) and least square-support vector machine (LS-SVM) was designed. Parameters, predetermined by conventional reaching law, were regulated by LS-SVM online. It was shown that system shattering is eliminated. Simulation results indicated that this method possesses the advantages of higher precision, greater adaptability and robustness, as compared to the conventional Variable Structure Control methods. © 2008 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE-
dc.relation.ispartof2008 IEEE Congress on Evolutionary Computation, CEC 2008en_HK
dc.titleIntelligent Variable Structure Control for Automated Guided Vehicleen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLin, MC:mcllin@hkucc.hku.hken_HK
dc.identifier.authorityLin, MC=rp00746en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/CEC.2008.4631337en_HK
dc.identifier.scopuseid_2-s2.0-55749104019en_HK
dc.identifier.hkuros145372en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-55749104019&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage3968en_HK
dc.identifier.epage3973en_HK
dc.identifier.scopusauthoridJiao, J=48662473500en_HK
dc.identifier.scopusauthoridChen, WW=23987423400en_HK
dc.identifier.scopusauthoridLeung, KS=7401860843en_HK
dc.identifier.scopusauthoridLi, SW=25640228200en_HK
dc.identifier.scopusauthoridWang, JX=8440014100en_HK
dc.identifier.scopusauthoridCheung, WKC=35080070600en_HK
dc.identifier.scopusauthoridLin, MC=7404816359en_HK
dc.identifier.issnl1089-778X-

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