Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model

Autores
González, Alejandro; Rivadeneira, Pablo; Ferramosca, Antonio; Magdelaine, Nicolas; Moog, Claude
Año de publicación
2020
Idioma
inglés
Tipo de recurso
parte de libro
Estado
versión borrador
Descripción
In this work the problem of regulating glycemia in type I diabetic patients is studied by means of an impulsive zone model predictive control (impulsive ZMPC) based on a novel long-term glucoseinsulin model. Taking advantage of the model - which features real life properties of diabetes patients that some other popular models do not - the proposed control ensures the stability under moderate-tosevere disturbances. A long-term scenario - including meals - are simulated, and the results appear to be satisfactory as long as every hyperglycemia and hypoglycemia episodes are suitably controlled.
Fil: Gonzales, Alejandro. CONICET - INTEC - Facultad de Ingeniería Química. Grupo de Control Avanzado de Procesos. Argentina
Fil: Ferramosca, Antonio. CONICET - UTN Facultad Regional Reconquista. Argentina.
Fil: Rivadeneira, Pablo. CONICET - INTEC - Facultad de Ingeniería Química, Grupo de Control Avanzado de Procesos. Argentina
Fil: Magdelaine, Nicolas. Universidad Nacional de Colombia, Facultad de Minas, Grupo GITA. Colombia.
Fil: Moog, Claude. L’UNAM Université, IRCCyN. France.
Peer Reviewed
Materia
Type I diabetes model, zone model predictive control, impulsive systems
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2021-03-11T21:09:30Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/4871
Acceder
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oai_identifier_str oai:ria.utn.edu.ar:20.500.12272/4871
network_acronym_str RIAUTN
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network_name_str Repositorio Institucional Abierto (UTN)
spelling Impulsive Zone MPC for Type I Diabetic Patients based on a long-term modelGonzález, AlejandroRivadeneira, PabloFerramosca, AntonioMagdelaine, NicolasMoog, ClaudeType I diabetes model, zone model predictive control, impulsive systemsIn this work the problem of regulating glycemia in type I diabetic patients is studied by means of an impulsive zone model predictive control (impulsive ZMPC) based on a novel long-term glucoseinsulin model. Taking advantage of the model - which features real life properties of diabetes patients that some other popular models do not - the proposed control ensures the stability under moderate-tosevere disturbances. A long-term scenario - including meals - are simulated, and the results appear to be satisfactory as long as every hyperglycemia and hypoglycemia episodes are suitably controlled.Fil: Gonzales, Alejandro. CONICET - INTEC - Facultad de Ingeniería Química. Grupo de Control Avanzado de Procesos. ArgentinaFil: Ferramosca, Antonio. CONICET - UTN Facultad Regional Reconquista. Argentina.Fil: Rivadeneira, Pablo. CONICET - INTEC - Facultad de Ingeniería Química, Grupo de Control Avanzado de Procesos. ArgentinaFil: Magdelaine, Nicolas. Universidad Nacional de Colombia, Facultad de Minas, Grupo GITA. Colombia.Fil: Moog, Claude. L’UNAM Université, IRCCyN. France.Peer ReviewedAhmad Taher Azar2021-03-11T21:09:30Z2021-03-11T21:09:30Z2020-02-01info:eu-repo/semantics/bookPartinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_3248info:ar-repo/semantics/parteDeLibroapplication/pdfapplication/pdfhttp://hdl.handle.net/20.500.12272/4871https://doi.org/10.1016/C2018-0-01351-1enginfo:eu-repo/semantics/openAccess2021-03-11T21:09:30ZN/Areponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:47:02Zoai:ria.utn.edu.ar:20.500.12272/4871instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:47:04.784Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
title Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
spellingShingle Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
González, Alejandro
Type I diabetes model, zone model predictive control, impulsive systems
title_short Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
title_full Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
title_fullStr Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
title_full_unstemmed Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
title_sort Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
dc.creator.none.fl_str_mv González, Alejandro
Rivadeneira, Pablo
Ferramosca, Antonio
Magdelaine, Nicolas
Moog, Claude
author González, Alejandro
author_facet González, Alejandro
Rivadeneira, Pablo
Ferramosca, Antonio
Magdelaine, Nicolas
Moog, Claude
author_role author
author2 Rivadeneira, Pablo
Ferramosca, Antonio
Magdelaine, Nicolas
Moog, Claude
author2_role author
author
author
author
dc.subject.none.fl_str_mv Type I diabetes model, zone model predictive control, impulsive systems
topic Type I diabetes model, zone model predictive control, impulsive systems
dc.description.none.fl_txt_mv In this work the problem of regulating glycemia in type I diabetic patients is studied by means of an impulsive zone model predictive control (impulsive ZMPC) based on a novel long-term glucoseinsulin model. Taking advantage of the model - which features real life properties of diabetes patients that some other popular models do not - the proposed control ensures the stability under moderate-tosevere disturbances. A long-term scenario - including meals - are simulated, and the results appear to be satisfactory as long as every hyperglycemia and hypoglycemia episodes are suitably controlled.
Fil: Gonzales, Alejandro. CONICET - INTEC - Facultad de Ingeniería Química. Grupo de Control Avanzado de Procesos. Argentina
Fil: Ferramosca, Antonio. CONICET - UTN Facultad Regional Reconquista. Argentina.
Fil: Rivadeneira, Pablo. CONICET - INTEC - Facultad de Ingeniería Química, Grupo de Control Avanzado de Procesos. Argentina
Fil: Magdelaine, Nicolas. Universidad Nacional de Colombia, Facultad de Minas, Grupo GITA. Colombia.
Fil: Moog, Claude. L’UNAM Université, IRCCyN. France.
Peer Reviewed
description In this work the problem of regulating glycemia in type I diabetic patients is studied by means of an impulsive zone model predictive control (impulsive ZMPC) based on a novel long-term glucoseinsulin model. Taking advantage of the model - which features real life properties of diabetes patients that some other popular models do not - the proposed control ensures the stability under moderate-tosevere disturbances. A long-term scenario - including meals - are simulated, and the results appear to be satisfactory as long as every hyperglycemia and hypoglycemia episodes are suitably controlled.
publishDate 2020
dc.date.none.fl_str_mv 2020-02-01
2021-03-11T21:09:30Z
2021-03-11T21:09:30Z
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/draft
http://purl.org/coar/resource_type/c_3248
info:ar-repo/semantics/parteDeLibro
format bookPart
status_str draft
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12272/4871
https://doi.org/10.1016/C2018-0-01351-1
url http://hdl.handle.net/20.500.12272/4871
https://doi.org/10.1016/C2018-0-01351-1
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2021-03-11T21:09:30Z
N/A
eu_rights_str_mv openAccess
rights_invalid_str_mv 2021-03-11T21:09:30Z
N/A
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Ahmad Taher Azar
publisher.none.fl_str_mv Ahmad Taher Azar
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.24418

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