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Conference Paper: Genetic design of fuzzy-logic controllers for robotic manipulators

TitleGenetic design of fuzzy-logic controllers for robotic manipulators
Authors
Porter, BZadeh, NN
KeywordsComputers
Artificial intelligence
Issue Date1995
PublisherIEEE.
Citation
IEEE International Conference on Evolutionary Computation Proceedings, Perth, WA, Australia, 29 November - 1 December 1995, v. 1, p. 267 How to Cite?
DOI: http://dx.doi.org/10.1109/ICEC.1995.489157
AbstractIn this paper, genetic algorithms are used to design multivariable fuzzy-logic controllers for robotic manipulators using no information regarding the dynamical parameters of such manipulators. In particular, it is shown that genetic algorithms provide a very effective means of determining both the optimal set of fuzzy rules and the domains of the associated fuzzy sets for such fuzzy-logic controllers. It is demonstrated, in the case of a particular direct-drive two-link robotic manipulator, that such fuzzy-logic controllers can be readily robustified.
Persistent Identifierhttp://hdl.handle.net/10722/46569

 

DC FieldValueLanguage
dc.contributor.authorPorter, Ben_HK
dc.contributor.authorZadeh, NNen_HK
dc.date.accessioned2007-10-30T06:53:08Z-
dc.date.available2007-10-30T06:53:08Z-
dc.date.issued1995en_HK
dc.identifier.citationIEEE International Conference on Evolutionary Computation Proceedings, Perth, WA, Australia, 29 November - 1 December 1995, v. 1, p. 267en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46569-
dc.description.abstractIn this paper, genetic algorithms are used to design multivariable fuzzy-logic controllers for robotic manipulators using no information regarding the dynamical parameters of such manipulators. In particular, it is shown that genetic algorithms provide a very effective means of determining both the optimal set of fuzzy rules and the domains of the associated fuzzy sets for such fuzzy-logic controllers. It is demonstrated, in the case of a particular direct-drive two-link robotic manipulator, that such fuzzy-logic controllers can be readily robustified.en_HK
dc.format.extent335044 bytes-
dc.format.extent4653 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rights©1995 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.-
dc.subjectComputersen_HK
dc.subjectArtificial intelligenceen_HK
dc.titleGenetic design of fuzzy-logic controllers for robotic manipulatorsen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICEC.1995.489157en_HK
dc.identifier.hkuros20993-

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