Feedback Linearization for a Generalized Multivariable T-S Model

This study presents a novel optimal fuzzy logic control (FLC) strategy based on feedback linearization for the regulation of multivariable nonlinear systems. Building upon an enhanced Takagi–Sugeno (T-S) model previously developed by the authors, the proposed method incorporates a refined parameter-...

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Detalles Bibliográficos
Autores: Al-Hadithi, Basil Mohammed, Blanco Rico, Javier, Jiménez, Agustín
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/418542
Acceso en línea:http://hdl.handle.net/10261/418542
Access Level:acceso abierto
Palabra clave:feedback linearization
multivariable systems
nonlinear systems
Takagi–Sugeno fuzzy model
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spelling Feedback Linearization for a Generalized Multivariable T-S ModelAl-Hadithi, Basil MohammedBlanco Rico, JavierJiménez, Agustínfeedback linearizationmultivariable systemsnonlinear systemsTakagi–Sugeno fuzzy modelThis study presents a novel optimal fuzzy logic control (FLC) strategy based on feedback linearization for the regulation of multivariable nonlinear systems. Building upon an enhanced Takagi–Sugeno (T-S) model previously developed by the authors, the proposed method incorporates a refined parameter-weighting scheme to optimize both local and global approximations within the T-S framework. This approach enables improved selection and minimization of the performance index. The effectiveness of the control strategy is validated through its application to a two-link serial robotic manipulator. The results demonstrate that the proposed FLC achieves robust performance, maintaining system stability and high accuracy even under the influence of noise and load disturbances, with well-damped system behavior and negligible steady-state error.Peer reviewedMultidisciplinary Digital Publishing InstituteAl-Hadithi, Basil Mohammed [0000-0002-8786-5511]Blanco Rico, Javier [0000-0002-0997-2821]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202620262025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/418542reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttps://doi.org/10.3390/electronics14153129Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4185422026-05-22T06:33:51Z
dc.title.none.fl_str_mv Feedback Linearization for a Generalized Multivariable T-S Model
title Feedback Linearization for a Generalized Multivariable T-S Model
spellingShingle Feedback Linearization for a Generalized Multivariable T-S Model
Al-Hadithi, Basil Mohammed
feedback linearization
multivariable systems
nonlinear systems
Takagi–Sugeno fuzzy model
title_short Feedback Linearization for a Generalized Multivariable T-S Model
title_full Feedback Linearization for a Generalized Multivariable T-S Model
title_fullStr Feedback Linearization for a Generalized Multivariable T-S Model
title_full_unstemmed Feedback Linearization for a Generalized Multivariable T-S Model
title_sort Feedback Linearization for a Generalized Multivariable T-S Model
dc.creator.none.fl_str_mv Al-Hadithi, Basil Mohammed
Blanco Rico, Javier
Jiménez, Agustín
author Al-Hadithi, Basil Mohammed
author_facet Al-Hadithi, Basil Mohammed
Blanco Rico, Javier
Jiménez, Agustín
author_role author
author2 Blanco Rico, Javier
Jiménez, Agustín
author2_role author
author
dc.contributor.none.fl_str_mv Al-Hadithi, Basil Mohammed [0000-0002-8786-5511]
Blanco Rico, Javier [0000-0002-0997-2821]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv feedback linearization
multivariable systems
nonlinear systems
Takagi–Sugeno fuzzy model
topic feedback linearization
multivariable systems
nonlinear systems
Takagi–Sugeno fuzzy model
description This study presents a novel optimal fuzzy logic control (FLC) strategy based on feedback linearization for the regulation of multivariable nonlinear systems. Building upon an enhanced Takagi–Sugeno (T-S) model previously developed by the authors, the proposed method incorporates a refined parameter-weighting scheme to optimize both local and global approximations within the T-S framework. This approach enables improved selection and minimization of the performance index. The effectiveness of the control strategy is validated through its application to a two-link serial robotic manipulator. The results demonstrate that the proposed FLC achieves robust performance, maintaining system stability and high accuracy even under the influence of noise and load disturbances, with well-damped system behavior and negligible steady-state error.
publishDate 2025
dc.date.none.fl_str_mv 2025
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/418542
url http://hdl.handle.net/10261/418542
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.3390/electronics14153129
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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