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dc.contributorDepartment of Electrical Engineering-
dc.creatorWong, LK-
dc.creatorLeung, FHF-
dc.creatorTam, PKS-
dc.rights© 1998 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.subjectClosed loop control systemsen_US
dc.subjectControl system analysisen_US
dc.subjectFuzzy setsen_US
dc.subjectParameter estimationen_US
dc.subjectRobustness (control systems)en_US
dc.subjectSystem stabilityen_US
dc.titleStability analysis of systems with parameter uncertainties under fuzzy logic controlen_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
dcterms.abstractSystems with parameter uncertainties are difficult to control. We propose a combined controller approach to tackle this problem. This approach involves designs of different controllers for different operation points. Then a fuzzy logic controller (FLC) is used to schedule these controllers according to the plant parameters. This FLC is different from the common FLCs in that plant parameters are used as the input variables in the premises of the fuzzy rules. Hence this FLC can tackle a large parameter change during operation. The resulting FLC will not only display good robustness but also lead to a stable closed-loop system. The stability will be proved by applying a new stability analysis method.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationThe 1998 IEEE International Conference on Fuzzy Systems proceedings : IEEE World Congress on Computational Intelligence : May 4-May 9, 1998, Anchorage, Alaska, USA, p. 446-450-
dc.relation.ispartofbookThe 1998 IEEE International Conference on Fuzzy Systems proceedings : IEEE World Congress on Computational Intelligence : May 4-May 9, 1998, Anchorage, Alaska, USA-
dc.relation.conferenceIEEE International Conference on Fuzzy Systems [FUZZ]-
dc.description.oaVersion of Recorden_US
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