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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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Al-Duwaish, H. (author)
مؤلفون آخرون: Karim, M.N. (author), Chandrasekar, V. (author), unknown (author)
التنسيق: article
منشور في: 1996
الموضوعات:
الوصول للمادة أونلاين: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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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