On-line identification of synchronous machines using radial basisfunction neural networks
On-line identification of the synchronous machines using radial basis function neural network (RBFNN) is presented in this paper. The capability of the proposed identifier to capture the nonlinear operating characteristics of the synchronous machine is illustrated. The results of the proposed identi...
محفوظ في:
| 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/14217/1/14217_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14217/2/14217_2.doc |
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| _version_ | 1864513402764787712 |
|---|---|
| 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 | 1997-11 2020 |
| dc.format.none.fl_str_mv | application/pdf application/msword |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14217/1/14217_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14217/2/14217_2.doc (1997) On-line identification of synchronous machines using radial basisfunction neural networks. Power Systems, IEEE Transactions on, 12. |
| 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/14217/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | On-line identification of synchronous machines using radial basisfunction neural networks |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | On-line identification of the synchronous machines using radial basis function neural network (RBFNN) is presented in this paper. The capability of the proposed identifier to capture the nonlinear operating characteristics of the synchronous machine is illustrated. The results of the proposed identifier performance due to square and uniformly distributed random variations in both mechanical torque and field voltage are compared with that obtained by time-domain simulations. Correlation-based model validity tests using residuals and inputs have been carried out to examine the validity of the proposed identifier. The results of these tests demonstrate the adequacy of the proposed identifier |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_5832d6667dd26209fee649aacf17ea76 |
| identifier_str_mv | (1997) On-line identification of synchronous machines using radial basisfunction neural networks. Power Systems, IEEE Transactions on, 12. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::14217 |
| publishDate | 1997 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | On-line identification of synchronous machines using radial basisfunction neural networksAbido, M.A.Abdel-Magid, Y.L.unknownComputerOn-line identification of the synchronous machines using radial basis function neural network (RBFNN) is presented in this paper. The capability of the proposed identifier to capture the nonlinear operating characteristics of the synchronous machine is illustrated. The results of the proposed identifier performance due to square and uniformly distributed random variations in both mechanical torque and field voltage are compared with that obtained by time-domain simulations. Correlation-based model validity tests using residuals and inputs have been carried out to examine the validity of the proposed identifier. The results of these tests demonstrate the adequacy of the proposed identifierIEEE1997-112020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14217/1/14217_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14217/2/14217_2.doc (1997) On-line identification of synchronous machines using radial basisfunction neural networks. Power Systems, IEEE Transactions on, 12. enenhttps://eprints.kfupm.edu.sa/id/eprint/14217/info:eu-repo/semantics/openAccessoai::142172019-11-01T14:04:45Z |
| spellingShingle | On-line identification of synchronous machines using radial basisfunction neural networks Abido, M.A. Computer |
| status_str | publishedVersion |
| title | On-line identification of synchronous machines using radial basisfunction neural networks |
| title_full | On-line identification of synchronous machines using radial basisfunction neural networks |
| title_fullStr | On-line identification of synchronous machines using radial basisfunction neural networks |
| title_full_unstemmed | On-line identification of synchronous machines using radial basisfunction neural networks |
| title_short | On-line identification of synchronous machines using radial basisfunction neural networks |
| title_sort | On-line identification of synchronous machines using radial basisfunction neural networks |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/14217/1/14217_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14217/2/14217_2.doc |