A fuzzy basis function network for generator excitation control

A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is trained over a wide range of operating conditio...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Abido, M.A. (author)
مؤلفون آخرون: Abdel-Magid, Y.L. (author), unknown (author)
التنسيق: article
منشور في: 1997
الموضوعات:
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/14474/1/14474_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14474/2/14474_2.doc
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author Abido, M.A.
author2 Abdel-Magid, Y.L.
unknown
author2_role author
author
author_facet Abido, M.A.
Abdel-Magid, Y.L.
unknown
author_role author
dc.creator.none.fl_str_mv Abido, M.A.
Abdel-Magid, Y.L.
unknown
dc.date.none.fl_str_mv 1997-07
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14474/1/14474_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14474/2/14474_2.doc
(1997) A fuzzy basis function network for generator excitation control. Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International conference, 3.
dc.language.none.fl_str_mv en
en
dc.publisher.none.fl_str_mv IEEE
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14474/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv A fuzzy basis function network for generator excitation control
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on generator loading conditions. The orthogonal least squares learning algorithm is developed for designing an adequate and parsimonious FBFN model. Time domain simulations of a synchronous machine equipped with the proposed stabilizer subject to major disturbances are investigated. The performance of the proposed FBFN based PSS is compared with that of a conventional power system stabilizer. The results show the robustness of the proposed FBFN PSS and its ability to enhance system damping over a wide range of operating conditions and system parameter variations
eu_rights_str_mv openAccess
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identifier_str_mv (1997) A fuzzy basis function network for generator excitation control. Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International conference, 3.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14474
publishDate 1997
publisher.none.fl_str_mv IEEE
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling A fuzzy basis function network for generator excitation controlAbido, M.A.Abdel-Magid, Y.L.unknownComputerA fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on generator loading conditions. The orthogonal least squares learning algorithm is developed for designing an adequate and parsimonious FBFN model. Time domain simulations of a synchronous machine equipped with the proposed stabilizer subject to major disturbances are investigated. The performance of the proposed FBFN based PSS is compared with that of a conventional power system stabilizer. The results show the robustness of the proposed FBFN PSS and its ability to enhance system damping over a wide range of operating conditions and system parameter variationsIEEE1997-072020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14474/1/14474_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14474/2/14474_2.doc (1997) A fuzzy basis function network for generator excitation control. Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International conference, 3. enenhttps://eprints.kfupm.edu.sa/id/eprint/14474/info:eu-repo/semantics/openAccessoai::144742019-11-01T14:05:57Z
spellingShingle A fuzzy basis function network for generator excitation control
Abido, M.A.
Computer
status_str publishedVersion
title A fuzzy basis function network for generator excitation control
title_full A fuzzy basis function network for generator excitation control
title_fullStr A fuzzy basis function network for generator excitation control
title_full_unstemmed A fuzzy basis function network for generator excitation control
title_short A fuzzy basis function network for generator excitation control
title_sort A fuzzy basis function network for generator excitation control
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14474/1/14474_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14474/2/14474_2.doc