Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems

Detalhes bibliográficos
Autor(a) principal: Chaudhary, Naveed Ishtiaq
Data de Publicação: 2021
Outros Autores: Raja, Muhammad Asif Zahoor, He, Yigang, Khan, Zeshan Aslam, Machado, J. A. Tenreiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/18604
Resumo: The development of procedures based on fractional calculus is an emerging research area. This paper presents a new perspective regarding the fractional least mean square (FLMS) adaptive algorithm, called multi innovation FLMS (MIFLMS). We verify that the iterative parameter adaptation mechanism of the FLMS uses merely the current error value (scalar innovation). The MIFLMS expands the scalar innovation into a vector innovation (error vector) by considering data over a fixed window at each iteration. Therefore, the MIFLMS yields better convergence speed than the standard FLMS by increasing the length of innovation vector. The superior performance of the MIFLMS is verified through parameter identification problem of input nonlinear systems. The statistical performance indices based on multiple independent trials confirm the consistent accuracy and reliability of the proposed scheme.
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spelling Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systemsFractional adaptive algorithmsParameter estimationInput nonlinear systemsMulti innovation theoryThe development of procedures based on fractional calculus is an emerging research area. This paper presents a new perspective regarding the fractional least mean square (FLMS) adaptive algorithm, called multi innovation FLMS (MIFLMS). We verify that the iterative parameter adaptation mechanism of the FLMS uses merely the current error value (scalar innovation). The MIFLMS expands the scalar innovation into a vector innovation (error vector) by considering data over a fixed window at each iteration. Therefore, the MIFLMS yields better convergence speed than the standard FLMS by increasing the length of innovation vector. The superior performance of the MIFLMS is verified through parameter identification problem of input nonlinear systems. The statistical performance indices based on multiple independent trials confirm the consistent accuracy and reliability of the proposed scheme.The authors are thankful to Dr. Ivan Markovsky for allowing us to use the results of the real experimentations conducted at the Southampton University [44–45]. This work was supported by the National Natural Science Foundation of China under Grant No. 51977153, 51977161, 51577046, the State Key Program of National Natural Science Foundation of China under Grant No. 51637004, National Key Research and Development Plan ”important scientific instruments and equipment development” Grant No. 2016YFF010220 and Equipment research project in advance Grant No 41402040301.ElsevierRepositório Científico do Instituto Politécnico do PortoChaudhary, Naveed IshtiaqRaja, Muhammad Asif ZahoorHe, YigangKhan, Zeshan AslamMachado, J. A. Tenreiro20212031-12-01T00:00:00Z2021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/18604eng10.1016/j.apm.2020.12.035info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T13:10:23Zoai:recipp.ipp.pt:10400.22/18604Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:38:09.631854Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
title Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
spellingShingle Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
Chaudhary, Naveed Ishtiaq
Fractional adaptive algorithms
Parameter estimation
Input nonlinear systems
Multi innovation theory
title_short Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
title_full Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
title_fullStr Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
title_full_unstemmed Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
title_sort Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems
author Chaudhary, Naveed Ishtiaq
author_facet Chaudhary, Naveed Ishtiaq
Raja, Muhammad Asif Zahoor
He, Yigang
Khan, Zeshan Aslam
Machado, J. A. Tenreiro
author_role author
author2 Raja, Muhammad Asif Zahoor
He, Yigang
Khan, Zeshan Aslam
Machado, J. A. Tenreiro
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Chaudhary, Naveed Ishtiaq
Raja, Muhammad Asif Zahoor
He, Yigang
Khan, Zeshan Aslam
Machado, J. A. Tenreiro
dc.subject.por.fl_str_mv Fractional adaptive algorithms
Parameter estimation
Input nonlinear systems
Multi innovation theory
topic Fractional adaptive algorithms
Parameter estimation
Input nonlinear systems
Multi innovation theory
description The development of procedures based on fractional calculus is an emerging research area. This paper presents a new perspective regarding the fractional least mean square (FLMS) adaptive algorithm, called multi innovation FLMS (MIFLMS). We verify that the iterative parameter adaptation mechanism of the FLMS uses merely the current error value (scalar innovation). The MIFLMS expands the scalar innovation into a vector innovation (error vector) by considering data over a fixed window at each iteration. Therefore, the MIFLMS yields better convergence speed than the standard FLMS by increasing the length of innovation vector. The superior performance of the MIFLMS is verified through parameter identification problem of input nonlinear systems. The statistical performance indices based on multiple independent trials confirm the consistent accuracy and reliability of the proposed scheme.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-01T00:00:00Z
2031-12-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/18604
url http://hdl.handle.net/10400.22/18604
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.apm.2020.12.035
dc.rights.driver.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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