Use of multilayer feedforward neural networks in identification andcontrol of Wiener model
The problem of identification and control of a Wiener model is studied. The proposed identification model uses a hybrid model consisting of a linear autoregressive moving average model in cascade with a multilayer feedforward neural network. A two-step procedure is proposed to estimate the linear an...
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1996
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| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/14330/1/14330_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14330/2/14330_2.doc |
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| _version_ | 1864513384096989184 |
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| author | Al-Duwaish, H. |
| author2 | Karim, M.N. Chandrasekar, V. unknown |
| author2_role | author author author |
| author_facet | Al-Duwaish, H. Karim, M.N. Chandrasekar, V. unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | Al-Duwaish, H. Karim, M.N. Chandrasekar, V. unknown |
| dc.date.none.fl_str_mv | 1996-05 2020 |
| dc.format.none.fl_str_mv | application/pdf application/msword |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14330/1/14330_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14330/2/14330_2.doc (1996) Use of multilayer feedforward neural networks in identification andcontrol of Wiener model. Control Theory and Applications, IEE Proceedings -, 143. |
| 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/14330/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | The problem of identification and control of a Wiener model is studied. The proposed identification model uses a hybrid model consisting of a linear autoregressive moving average model in cascade with a multilayer feedforward neural network. A two-step procedure is proposed to estimate the linear and nonlinear parts separately. Control of the Wiener model can be achieved by inserting the inverse of the static nonlinearity in the appropriate loop locations. Simulation results illustrate the performance of the proposed method |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_7865b1dcc02ab99596d800e410d6c82a |
| identifier_str_mv | (1996) Use of multilayer feedforward neural networks in identification andcontrol of Wiener model. Control Theory and Applications, IEE Proceedings -, 143. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::14330 |
| publishDate | 1996 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Use of multilayer feedforward neural networks in identification andcontrol of Wiener modelAl-Duwaish, H.Karim, M.N.Chandrasekar, V.unknownComputerThe problem of identification and control of a Wiener model is studied. The proposed identification model uses a hybrid model consisting of a linear autoregressive moving average model in cascade with a multilayer feedforward neural network. A two-step procedure is proposed to estimate the linear and nonlinear parts separately. Control of the Wiener model can be achieved by inserting the inverse of the static nonlinearity in the appropriate loop locations. Simulation results illustrate the performance of the proposed methodIEEE1996-052020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14330/1/14330_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14330/2/14330_2.doc (1996) Use of multilayer feedforward neural networks in identification andcontrol of Wiener model. Control Theory and Applications, IEE Proceedings -, 143. enenhttps://eprints.kfupm.edu.sa/id/eprint/14330/info:eu-repo/semantics/openAccessoai::143302019-11-01T14:05:22Z |
| spellingShingle | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model Al-Duwaish, H. Computer |
| status_str | publishedVersion |
| title | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model |
| title_full | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model |
| title_fullStr | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model |
| title_full_unstemmed | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model |
| title_short | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model |
| title_sort | Use of multilayer feedforward neural networks in identification andcontrol of Wiener model |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/14330/1/14330_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14330/2/14330_2.doc |