Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA

In this degree work, an adjustment method called Lambda Tuning, widely used in PID control algorithms at an industrial level, was studied for the control of glycemia in patients with type 1 diabetes. Two controllers were implemented, a PID and a PD- basal, which were used for glycemic control of the...

Full description

Autores:
Gamez Peña, Yeferson Yovani
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2022
Institución:
Universidad Antonio Nariño
Repositorio:
Repositorio UAN
Idioma:
spa
OAI Identifier:
oai:repositorio.uan.edu.co:123456789/7220
Acceso en línea:
http://repositorio.uan.edu.co/handle/123456789/7220
Palabra clave:
Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
Rights
openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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oai_identifier_str oai:repositorio.uan.edu.co:123456789/7220
network_acronym_str UAntonioN2
network_name_str Repositorio UAN
repository_id_str
dc.title.es_ES.fl_str_mv Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
title Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
spellingShingle Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
title_short Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
title_full Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
title_fullStr Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
title_full_unstemmed Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
title_sort Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDA
dc.creator.fl_str_mv Gamez Peña, Yeferson Yovani
dc.contributor.advisor.spa.fl_str_mv León Vargas, Fabian Mauricio
Rodríguez Sarmiento, David Leonardo
dc.contributor.author.spa.fl_str_mv Gamez Peña, Yeferson Yovani
dc.subject.es_ES.fl_str_mv Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
topic Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
dc.subject.keyword.es_ES.fl_str_mv Lambda,
PID,
Glucemia,
PD-basal,
Uva-Padova.
description In this degree work, an adjustment method called Lambda Tuning, widely used in PID control algorithms at an industrial level, was studied for the control of glycemia in patients with type 1 diabetes. Two controllers were implemented, a PID and a PD- basal, which were used for glycemic control of the average adult patient with type 1 diabetes that is virtually included in the Uva-Padova simulator, approved by the Food and Drug Administration (FDA) as a substitute for conducting preclinical trials in animals. For the application of the Lambda method, first order models plus dead time were determined for the average adult patient of the Uva-Padova simulator in different operating conditions (operating points). These models were used to adjust the PID and PD-basal controllers. Finally, an evaluation of the performance of the controllers and of each control configuration was carried out under different test conditions (scenario of one and three meals). The performance obtained was analyzed according to metrics such as time in normoglycemia and percentage of time in hypoglycemia. It is expected that, thanks to the completion of this project, new adjustment alternatives for PID controllers can be implemented in Artificial Pancreas systems.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-11-04T22:26:13Z
dc.date.available.none.fl_str_mv 2022-11-04T22:26:13Z
dc.date.issued.spa.fl_str_mv 2022-04-08
dc.type.spa.fl_str_mv Trabajo de grado (Pregrado y/o Especialización)
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
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format http://purl.org/coar/resource_type/c_7a1f
dc.identifier.uri.none.fl_str_mv http://repositorio.uan.edu.co/handle/123456789/7220
dc.identifier.bibliographicCitation.spa.fl_str_mv Bondia, J., Vehí, J., Palerm, C. C., & Herrero, P. (2010). El Ṕancreas Artificial: Control Autoḿatico de Infusíon de Insulina en Diabetes Mellitus Tipo 1. RIAI - Revista Iberoamericana de Automatica e Informatica Industrial. https://doi.org/10.4995/RIAI.2010.02.01
Colmegna, P., Sánchez-Peña, R. S., & Gondhalekar, R. (2018). Linear parameter-varying model to design control laws for an artificial pancreas. Biomedical Signal Processing and Control, 40, 208–213. https://doi.org/10.1016/J.BSPC.2017.09.021
Cooper, D. J. (2005). Practical Process Control using Loop-Pro Software. In Control Station, Inc. One Technology drive
Dalla Man, C., Micheletto, F., Lv, D., Breton, M., Kovatchev, B., & Cobelli, C. (2014). The UVA/PADOVA Type 1 Diabetes Simulator: New Features. Journal of Diabetes Science and Technology, 8. https://doi.org/10.1177/1932296813514502
Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., Garg, S., Heinemann, L., Hirsch, I., Amiel, S. A., Beck, R., Bosi, E., Buckingham, B., Cobelli, C., Dassau, E., Doyle, F. J., Heller, S., Hovorka, R., Jia, W., … Phillip, M. (2017). International Consensus on Use of Continuous Glucose Monitoring. Diabetes Care, 40(12), 1631–1640. https://doi.org/10.2337/DC17- 1600
International Diabetes Federation. (2019). ATLAS DE LA DIABETES. Atlas de La Diabetes de La FID, 9, 1–180. https://diabetesatlas.org/es/
Karl Johan, Å., Tore, H., Kuo, B., Chen, C.-T., Paraskevopoulos, P. N., Paraskevopoulos, P. N., E.LeBlanc Steven, D. R. C., Goodwin, G. C., Graebe, S. F., Salgado, M. E., Morilla García, F., Rodríguez Rubio, F., Ortega Linares, M., Scharfstein, M., Gaurf, A, M. E. C. A. T. R. Ó. N. I. C., Walter, J., Dulhoste, J., Bomstein, Y., … Muños-Sánchez, Y. (2009). Control PID avanzado. In Modern Control Engineering (Vol. 23, Issue 4). PEARSON EDUACIÓN,S.A.
León Vargas, F., Garelli, F., De Battista, H., & Vehí, J. (2013). Postprandial blood glucose control using a hybrid adaptive PD controller with insulin-on-board limitation. Biomedical Signal Processing and Control, 8. https://doi.org/10.1016/j.bspc.2013.06.008
Molano Jimenez, A., & León Vargas, F. (2017). Uva/Padova T1DMS dynamic model revision: For embedded model control. 2017 IEEE 3rd Colombian Conference on Automatic Control, CCAC 2017 - Conference Proceedings, 2018-Janua, 1–6. https://doi.org/10.1109/CCAC.2017.8276390
dc.identifier.instname.spa.fl_str_mv instname:Universidad Antonio Nariño
dc.identifier.reponame.spa.fl_str_mv reponame:Repositorio Institucional UAN
dc.identifier.repourl.spa.fl_str_mv repourl:https://repositorio.uan.edu.co/
url http://repositorio.uan.edu.co/handle/123456789/7220
identifier_str_mv Bondia, J., Vehí, J., Palerm, C. C., & Herrero, P. (2010). El Ṕancreas Artificial: Control Autoḿatico de Infusíon de Insulina en Diabetes Mellitus Tipo 1. RIAI - Revista Iberoamericana de Automatica e Informatica Industrial. https://doi.org/10.4995/RIAI.2010.02.01
Colmegna, P., Sánchez-Peña, R. S., & Gondhalekar, R. (2018). Linear parameter-varying model to design control laws for an artificial pancreas. Biomedical Signal Processing and Control, 40, 208–213. https://doi.org/10.1016/J.BSPC.2017.09.021
Cooper, D. J. (2005). Practical Process Control using Loop-Pro Software. In Control Station, Inc. One Technology drive
Dalla Man, C., Micheletto, F., Lv, D., Breton, M., Kovatchev, B., & Cobelli, C. (2014). The UVA/PADOVA Type 1 Diabetes Simulator: New Features. Journal of Diabetes Science and Technology, 8. https://doi.org/10.1177/1932296813514502
Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., Garg, S., Heinemann, L., Hirsch, I., Amiel, S. A., Beck, R., Bosi, E., Buckingham, B., Cobelli, C., Dassau, E., Doyle, F. J., Heller, S., Hovorka, R., Jia, W., … Phillip, M. (2017). International Consensus on Use of Continuous Glucose Monitoring. Diabetes Care, 40(12), 1631–1640. https://doi.org/10.2337/DC17- 1600
International Diabetes Federation. (2019). ATLAS DE LA DIABETES. Atlas de La Diabetes de La FID, 9, 1–180. https://diabetesatlas.org/es/
Karl Johan, Å., Tore, H., Kuo, B., Chen, C.-T., Paraskevopoulos, P. N., Paraskevopoulos, P. N., E.LeBlanc Steven, D. R. C., Goodwin, G. C., Graebe, S. F., Salgado, M. E., Morilla García, F., Rodríguez Rubio, F., Ortega Linares, M., Scharfstein, M., Gaurf, A, M. E. C. A. T. R. Ó. N. I. C., Walter, J., Dulhoste, J., Bomstein, Y., … Muños-Sánchez, Y. (2009). Control PID avanzado. In Modern Control Engineering (Vol. 23, Issue 4). PEARSON EDUACIÓN,S.A.
León Vargas, F., Garelli, F., De Battista, H., & Vehí, J. (2013). Postprandial blood glucose control using a hybrid adaptive PD controller with insulin-on-board limitation. Biomedical Signal Processing and Control, 8. https://doi.org/10.1016/j.bspc.2013.06.008
Molano Jimenez, A., & León Vargas, F. (2017). Uva/Padova T1DMS dynamic model revision: For embedded model control. 2017 IEEE 3rd Colombian Conference on Automatic Control, CCAC 2017 - Conference Proceedings, 2018-Janua, 1–6. https://doi.org/10.1109/CCAC.2017.8276390
instname:Universidad Antonio Nariño
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dc.coverage.spatial.spa.fl_str_mv Colombia(Bogotá,Dc)
dc.publisher.spa.fl_str_mv Universidad Antonio Nariño
dc.publisher.program.spa.fl_str_mv Ingeniería en Control y Automatización Industrial
dc.publisher.faculty.spa.fl_str_mv Facultad de Ingeniería Mecánica, Electrónica y Biomédica
dc.publisher.campus.spa.fl_str_mv Bogotá - Sur
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spelling Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)Acceso abiertohttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2León Vargas, Fabian MauricioRodríguez Sarmiento, David LeonardoGamez Peña, Yeferson Yovani11291727490Colombia(Bogotá,Dc)2022-11-04T22:26:13Z2022-11-04T22:26:13Z2022-04-08http://repositorio.uan.edu.co/handle/123456789/7220Bondia, J., Vehí, J., Palerm, C. C., & Herrero, P. (2010). El Ṕancreas Artificial: Control Autoḿatico de Infusíon de Insulina en Diabetes Mellitus Tipo 1. RIAI - Revista Iberoamericana de Automatica e Informatica Industrial. https://doi.org/10.4995/RIAI.2010.02.01Colmegna, P., Sánchez-Peña, R. S., & Gondhalekar, R. (2018). Linear parameter-varying model to design control laws for an artificial pancreas. Biomedical Signal Processing and Control, 40, 208–213. https://doi.org/10.1016/J.BSPC.2017.09.021Cooper, D. J. (2005). Practical Process Control using Loop-Pro Software. In Control Station, Inc. One Technology driveDalla Man, C., Micheletto, F., Lv, D., Breton, M., Kovatchev, B., & Cobelli, C. (2014). The UVA/PADOVA Type 1 Diabetes Simulator: New Features. Journal of Diabetes Science and Technology, 8. https://doi.org/10.1177/1932296813514502Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., Garg, S., Heinemann, L., Hirsch, I., Amiel, S. A., Beck, R., Bosi, E., Buckingham, B., Cobelli, C., Dassau, E., Doyle, F. J., Heller, S., Hovorka, R., Jia, W., … Phillip, M. (2017). International Consensus on Use of Continuous Glucose Monitoring. Diabetes Care, 40(12), 1631–1640. https://doi.org/10.2337/DC17- 1600International Diabetes Federation. (2019). ATLAS DE LA DIABETES. Atlas de La Diabetes de La FID, 9, 1–180. https://diabetesatlas.org/es/Karl Johan, Å., Tore, H., Kuo, B., Chen, C.-T., Paraskevopoulos, P. N., Paraskevopoulos, P. N., E.LeBlanc Steven, D. R. C., Goodwin, G. C., Graebe, S. F., Salgado, M. E., Morilla García, F., Rodríguez Rubio, F., Ortega Linares, M., Scharfstein, M., Gaurf, A, M. E. C. A. T. R. Ó. N. I. C., Walter, J., Dulhoste, J., Bomstein, Y., … Muños-Sánchez, Y. (2009). Control PID avanzado. In Modern Control Engineering (Vol. 23, Issue 4). PEARSON EDUACIÓN,S.A.León Vargas, F., Garelli, F., De Battista, H., & Vehí, J. (2013). Postprandial blood glucose control using a hybrid adaptive PD controller with insulin-on-board limitation. Biomedical Signal Processing and Control, 8. https://doi.org/10.1016/j.bspc.2013.06.008Molano Jimenez, A., & León Vargas, F. (2017). Uva/Padova T1DMS dynamic model revision: For embedded model control. 2017 IEEE 3rd Colombian Conference on Automatic Control, CCAC 2017 - Conference Proceedings, 2018-Janua, 1–6. https://doi.org/10.1109/CCAC.2017.8276390instname:Universidad Antonio Nariñoreponame:Repositorio Institucional UANrepourl:https://repositorio.uan.edu.co/In this degree work, an adjustment method called Lambda Tuning, widely used in PID control algorithms at an industrial level, was studied for the control of glycemia in patients with type 1 diabetes. Two controllers were implemented, a PID and a PD- basal, which were used for glycemic control of the average adult patient with type 1 diabetes that is virtually included in the Uva-Padova simulator, approved by the Food and Drug Administration (FDA) as a substitute for conducting preclinical trials in animals. For the application of the Lambda method, first order models plus dead time were determined for the average adult patient of the Uva-Padova simulator in different operating conditions (operating points). These models were used to adjust the PID and PD-basal controllers. Finally, an evaluation of the performance of the controllers and of each control configuration was carried out under different test conditions (scenario of one and three meals). The performance obtained was analyzed according to metrics such as time in normoglycemia and percentage of time in hypoglycemia. It is expected that, thanks to the completion of this project, new adjustment alternatives for PID controllers can be implemented in Artificial Pancreas systems.En este trabajo de grado, se estudió un método de ajuste llamado Lambda Tuning, ampliamente utilizado en algoritmos de control PID a nivel industrial, para el control de glucemia de pacientes con diabetes tipo 1. Se implementaron dos controladores, un PID y un PD-basal, que fueron utilizados para el control de la glucemia del paciente adulto promedio con diabetes tipo 1 que se incluye virtualmente en el simulador Uva-Padova, aprobado por la Administración de Medicamentos y Alimentos (FDA) como sustituto para la realización de ensayos preclínicos en animales. Para la aplicación del método Lambda se determinaron modelos de primer orden más tiempo muerto, para el paciente adulto promedio del simulador Uva-Padova en distintas condiciones de operación (puntos de operación). Estos modelos fueron utilizados para el ajuste de los controladores PID y PD-basal. Finalmente se realizó una evaluación del desempeño de los controladores y de cada configuración de control sobre distintas condiciones de prueba (escenario de una y tres comidas). Se analizó el desempeño obtenido de acuerdo con métricas como tiempo en normoglucemia y porcentaje de tiempo en hipoglucemia. Se espera que, gracias a la realización de este proyecto, nuevas alternativas de ajuste de controladores PID puedan ser implementadas en sistemas de Páncreas Artificial.Ingeniero(a) en Control y Automatización IndustrialPregradoPresencialInvestigaciónspaUniversidad Antonio NariñoIngeniería en Control y Automatización IndustrialFacultad de Ingeniería Mecánica, Electrónica y BiomédicaBogotá - SurLambda,PID,Glucemia,PD-basal,Uva-Padova.Lambda,PID,Glucemia,PD-basal,Uva-Padova.Evaluación de controladores PID para el control de glucemia de pacientes con diabetes tipo 1 a partir de sincronizaciones mediante el método LAMBDATrabajo de grado (Pregrado y/o Especialización)http://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_970fb48d4fbd8a85GeneralCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repositorio.uan.edu.co/bitstreams/850c9d03-0be7-4b5f-9900-096ece42c825/download9868ccc48a14c8d591352b6eaf7f6239MD54ORIGINAL2022_Acta-Gamez.pdf2022_Acta-Gamez.pdfActa de tesisapplication/pdf333956https://repositorio.uan.edu.co/bitstreams/ae9c8fd7-e288-49c7-aa98-8bc3cb8fc4c5/downloadbca7f6b912242363855d86e2d47e67f4MD512022_Autorización-Gamez.pdf2022_Autorización-Gamez.pdfAutorización autoresapplication/pdf1083540https://repositorio.uan.edu.co/bitstreams/96a14ef2-1bf6-4de1-8a30-461c0f71bfc3/downloadfe43d0159490ffd5d8d9f82af0b2fc4aMD522022_TIG-Gamez.pdf2022_TIG-Gamez.pdfTrabajo de gradoapplication/pdf2251783https://repositorio.uan.edu.co/bitstreams/556fc979-337f-4bfa-859f-7d9fa4e64267/download736c45b2129e8f899fa5023e512532e5MD53123456789/7220oai:repositorio.uan.edu.co:123456789/72202024-10-09 23:28:40.817https://creativecommons.org/licenses/by-nc-nd/4.0/Acceso abiertorestrictedhttps://repositorio.uan.edu.coRepositorio Institucional UANalertas.repositorio@uan.edu.co

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