Observer-based adaptive control using multiple-models switching and tuning

Autores
Giovanini, Leonardo Luis; Sanchez, Guido Marcelo; Benosman, Mouhacine
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Despite the remarkable theoretical accomplishments and successful applications of adaptive control, this field is not mature enough to solve challenging problems where strict performance and robustness guarantees are required. The needs of an approach that explicitly accounts for robust performance and stability specifications is a critical to the design of practical adaptive control systems. Towards this goal, this study extends the robust adaptive controller using multiple models, switching and tuning to multiple input multiple output and non-linear systems. The use of `extended superstability', instead of superstability, allows us to establish overall performance guarantees and reduce the conservativeness of the resulting closed-loop system. The authors show that under the proposed framework, the output and states remain bounded for bounded disturbances, as a direct consequence of the passivation properties of superstability. The effectiveness of the proposed algorithm is demonstrated in numerical simulations of a non-linear continuous stirred tank reactor.
Fil: Giovanini, Leonardo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Sanchez, Guido Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Benosman, Mouhacine. National University of Singapore; Singapur
Materia
Observers
Adaptive Control
Control System Synthesis
Mimo Time-Varying Systems
Nonlinear Control Systems
Robust Control
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/31543
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/31543
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Observer-based adaptive control using multiple-models switching and tuningGiovanini, Leonardo LuisSanchez, Guido MarceloBenosman, MouhacineObserversAdaptive ControlControl System SynthesisMimo Time-Varying SystemsNonlinear Control SystemsRobust Controlhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Despite the remarkable theoretical accomplishments and successful applications of adaptive control, this field is not mature enough to solve challenging problems where strict performance and robustness guarantees are required. The needs of an approach that explicitly accounts for robust performance and stability specifications is a critical to the design of practical adaptive control systems. Towards this goal, this study extends the robust adaptive controller using multiple models, switching and tuning to multiple input multiple output and non-linear systems. The use of `extended superstability', instead of superstability, allows us to establish overall performance guarantees and reduce the conservativeness of the resulting closed-loop system. The authors show that under the proposed framework, the output and states remain bounded for bounded disturbances, as a direct consequence of the passivation properties of superstability. The effectiveness of the proposed algorithm is demonstrated in numerical simulations of a non-linear continuous stirred tank reactor.Fil: Giovanini, Leonardo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Sanchez, Guido Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Benosman, Mouhacine. National University of Singapore; SingapurInstitution of Engineering and Technology2014-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/31543Giovanini, Leonardo Luis; Sanchez, Guido Marcelo; Benosman, Mouhacine; Observer-based adaptive control using multiple-models switching and tuning; Institution of Engineering and Technology; IET Control Theory and Applications; 8; 4; 2-2014; 235-2471751-86441751-8652CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1049/iet-cta.2013.0242info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:16:43Zoai:ri.conicet.gov.ar:11336/31543instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:16:43.288CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Observer-based adaptive control using multiple-models switching and tuning
title Observer-based adaptive control using multiple-models switching and tuning
spellingShingle Observer-based adaptive control using multiple-models switching and tuning
Giovanini, Leonardo Luis
Observers
Adaptive Control
Control System Synthesis
Mimo Time-Varying Systems
Nonlinear Control Systems
Robust Control
title_short Observer-based adaptive control using multiple-models switching and tuning
title_full Observer-based adaptive control using multiple-models switching and tuning
title_fullStr Observer-based adaptive control using multiple-models switching and tuning
title_full_unstemmed Observer-based adaptive control using multiple-models switching and tuning
title_sort Observer-based adaptive control using multiple-models switching and tuning
dc.creator.none.fl_str_mv Giovanini, Leonardo Luis
Sanchez, Guido Marcelo
Benosman, Mouhacine
author Giovanini, Leonardo Luis
author_facet Giovanini, Leonardo Luis
Sanchez, Guido Marcelo
Benosman, Mouhacine
author_role author
author2 Sanchez, Guido Marcelo
Benosman, Mouhacine
author2_role author
author
dc.subject.none.fl_str_mv Observers
Adaptive Control
Control System Synthesis
Mimo Time-Varying Systems
Nonlinear Control Systems
Robust Control
topic Observers
Adaptive Control
Control System Synthesis
Mimo Time-Varying Systems
Nonlinear Control Systems
Robust Control
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Despite the remarkable theoretical accomplishments and successful applications of adaptive control, this field is not mature enough to solve challenging problems where strict performance and robustness guarantees are required. The needs of an approach that explicitly accounts for robust performance and stability specifications is a critical to the design of practical adaptive control systems. Towards this goal, this study extends the robust adaptive controller using multiple models, switching and tuning to multiple input multiple output and non-linear systems. The use of `extended superstability', instead of superstability, allows us to establish overall performance guarantees and reduce the conservativeness of the resulting closed-loop system. The authors show that under the proposed framework, the output and states remain bounded for bounded disturbances, as a direct consequence of the passivation properties of superstability. The effectiveness of the proposed algorithm is demonstrated in numerical simulations of a non-linear continuous stirred tank reactor.
Fil: Giovanini, Leonardo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Sanchez, Guido Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Benosman, Mouhacine. National University of Singapore; Singapur
description Despite the remarkable theoretical accomplishments and successful applications of adaptive control, this field is not mature enough to solve challenging problems where strict performance and robustness guarantees are required. The needs of an approach that explicitly accounts for robust performance and stability specifications is a critical to the design of practical adaptive control systems. Towards this goal, this study extends the robust adaptive controller using multiple models, switching and tuning to multiple input multiple output and non-linear systems. The use of `extended superstability', instead of superstability, allows us to establish overall performance guarantees and reduce the conservativeness of the resulting closed-loop system. The authors show that under the proposed framework, the output and states remain bounded for bounded disturbances, as a direct consequence of the passivation properties of superstability. The effectiveness of the proposed algorithm is demonstrated in numerical simulations of a non-linear continuous stirred tank reactor.
publishDate 2014
dc.date.none.fl_str_mv 2014-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/31543
Giovanini, Leonardo Luis; Sanchez, Guido Marcelo; Benosman, Mouhacine; Observer-based adaptive control using multiple-models switching and tuning; Institution of Engineering and Technology; IET Control Theory and Applications; 8; 4; 2-2014; 235-247
1751-8644
1751-8652
CONICET Digital
CONICET
url http://hdl.handle.net/11336/31543
identifier_str_mv Giovanini, Leonardo Luis; Sanchez, Guido Marcelo; Benosman, Mouhacine; Observer-based adaptive control using multiple-models switching and tuning; Institution of Engineering and Technology; IET Control Theory and Applications; 8; 4; 2-2014; 235-247
1751-8644
1751-8652
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1049/iet-cta.2013.0242
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institution of Engineering and Technology
publisher.none.fl_str_mv Institution of Engineering and Technology
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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