Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1390
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dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorLeung, FHF-
dc.creatorLam, HK-
dc.creatorTam, PKS-
dc.creatorLee, YS-
dc.date.accessioned2014-12-11T08:26:24Z-
dc.date.available2014-12-11T08:26:24Z-
dc.identifier.isbn0-7803-7810-5-
dc.identifier.urihttp://hdl.handle.net/10397/1390-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2003 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_US
dc.rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en_US
dc.subjectComputer simulationen_US
dc.subjectFeedback controlen_US
dc.subjectFuzzy setsen_US
dc.subjectGenetic algorithmsen_US
dc.subjectNonlinear control systemsen_US
dc.subjectSystem stabilityen_US
dc.titleStable fuzzy controller design for uncertain nonlinear systems : genetic algorithm approachen_US
dc.typeConference Paperen_US
dc.description.otherinformationAuthor name used in this publication: F. H. F. Leungen_US
dc.description.otherinformationAuthor name used in this publication: P. K. S. Tamen_US
dc.description.otherinformationAuthor name used in this publication: Y. S. Leeen_US
dc.description.otherinformationCentre for Multimedia Signal Processing, Department of Electronic and Information Engineeringen_US
dc.description.otherinformationRefereed conference paperen_US
dcterms.abstractThis paper addresses the stable fuzzy controller design problem of nonlinear systems. The methodology is based on a fuzzy logic approach and the genetic algorithm (GA). In order to analyze the system stability, the TSK fuzzy plant model is employed to describe the dynamics of the nonlinear plant. A fuzzy controller is then developed to close the feedback loop. The stability conditions are derived. The feedback gains of the fuzzy controller and the solution for meeting the stability conditions are determined using the GA. An application example on stabilizing an inverted pendulum system will be given. Simulation and experimental results will be presented to verify the applicability of the proposed approach.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationFUZZ-IEEE 2003 : proceedings of the 12th IEEE International Conference on Fuzzy Systems : Sunday 25 May-Wednesday 28 May, 2003, St. Louis, Missouri, USA, p. 500-505-
dcterms.issued2003-
dc.identifier.isiWOS:000183448800087-
dc.identifier.scopus2-s2.0-0037523480-
dc.relation.ispartofbookFUZZ-IEEE 2003 : proceedings of the 12th IEEE International Conference on Fuzzy Systems : Sunday 25 May-Wednesday 28 May, 2003, St. Louis, Missouri, USA-
dc.relation.conferenceIEEE International Conference on Fuzzy Systems [FUZZ]-
dc.identifier.rosgroupidr14361-
dc.description.ros2002-2003 > Academic research: refereed > Refereed conference paper-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryVoR alloweden_US
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