Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1395
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dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorLam, HK-
dc.creatorLeung, FHF-
dc.date.accessioned2014-12-11T08:26:23Z-
dc.date.available2014-12-11T08:26:23Z-
dc.identifier.isbn0-7803-8730-9-
dc.identifier.urihttp://hdl.handle.net/10397/1395-
dc.language.isoenen_US
dc.publisherIEEEen_US
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_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.subjectControl equipmenten_US
dc.subjectControl systemsen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMatrix algebraen_US
dc.subjectNonlinear systemsen_US
dc.subjectOptimizationen_US
dc.subjectPendulumsen_US
dc.titleStability analysis, synthesis and optimization of radial-basis-function neural-network based controller for nonlinear systemsen_US
dc.typeConference Paperen_US
dc.description.otherinformationAuthor name used in this publication: F. H. F. Leungen_US
dc.description.otherinformationCentre for Multimedia Signal Processing, Department of Electronic and Information Engineeringen_US
dc.description.otherinformationRefereed conference paperen_US
dcterms.abstractThis paper presents the stability analysis, synthesis, and performance optimization of a radial-basis-function neural-network based control system. Global stability conditions will be derived in terms of matrix measure. Based on the derived stability conditions, connection weights of the radial-basis-function neural-network based controller can be optimized by genetic algorithm (GA) subject to the system stability. Furthermore, the system performance will also be optimized by the GA. An application example on stabilizing an inverted pendulum will be given to illustrate the design procedure and merits of the proposed approach.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIECON 2004 : 30th annual conference of IEEE Industrial Electronics Society : Busan, South Korea, 2-6 November 2004, p. 2813-2818-
dcterms.issued2004-
dc.identifier.isiWOS:000299171300156-
dc.identifier.scopus2-s2.0-20544467250-
dc.identifier.rosgroupidr22392-
dc.description.ros2004-2005 > Academic research: refereed > Refereed conference paper-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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