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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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | article |
| منشور في: |
1997
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| 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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| _version_ | 1864513393797365760 |
|---|---|
| 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 |
| format | article |
| id | KFUPM_1aa5a9167ec978ddd700cc21ce7c070d |
| 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 |