Publicado

2018-10-01

Artificial pancreas: glycemic control strategies for avoiding hypoglycemia

Páncreas artificial: estrategias de control glucémico que evitan hipoglucemia

DOI:

https://doi.org/10.15446/dyna.v85n207.71535

Palabras clave:

artificial pancreas, diabetes mellitus type 1, PID control, model predictive control, performance, robustness (en)
páncreas artificial, diabetes mellitus tipo 1, control PID, control predictivo basado en modelo, desempeño, robustez (es)

Autores/as

This paper examines the performance of two new closed-loop control strategies developed as part of the Artificial Pancreas project, this being the most promising treatment for type 1 diabetes mellitus. The first strategy uses a new version of the well-known proportional, integral and derivative control, developed to respect state and input positivity constraints. The second is a new formulation of model-based predictive control with an impulsive input. The strategies’ performance is evaluated with 50 virtual patients taken from the literature and the UVa/Padova metabolic simulator, approved by the US Food and Drug Administration. Also, a robustness analysis is added to evaluate the strategies under the parametric variations of the most important physiological parameters. The results show that both strategies have a good performance with low to moderate plant-model mismatch.
Este trabajo presenta un análisis de desempeño de dos nuevos algoritmos de control desarrollados como parte del proyecto conocido como “Páncreas Artificial”, siendo este el tratamiento más promisorio para la diabetes mellitus tipo 1. Se desarrolló una versión del controlador proporcional, integral y derivativo el cual cumple restricciones de positividad en los estados y entradas, además de una nueva versión impulsiva del control predictivo basado en modelo. El desempeño de las estrategias es evaluado en 50 pacientes virtuales extraídos de la literatura y del Simulador UVa/Padova aprobado por la Food and Drug Administration de EEUU. La robustez se evalúa realizando variaciones paramétricas en los parámetros importantes del modelo. Las estrategias se validan en el simulador considerando diferencia planta-modelo. Los resultados muestran que el control predictivo presenta mejor desempeño, pero puede presentar infactibilidad si aumenta la diferencia planta-modelo. En contraste, el controlador proporcional, integral y derivativo presenta una respuesta más rápida, manteniendo un desempeño aceptable bajo perturbaciones de comida y seguimiento de referencia.

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Cómo citar

IEEE

[1]
J. E. Sereno, M. A. Caicedo, y P. S. Rivadeneira, «Artificial pancreas: glycemic control strategies for avoiding hypoglycemia», DYNA, vol. 85, n.º 207, pp. 198–207, oct. 2018.

ACM

[1]
Sereno, J.E., Caicedo, M.A. y Rivadeneira, P.S. 2018. Artificial pancreas: glycemic control strategies for avoiding hypoglycemia. DYNA. 85, 207 (oct. 2018), 198–207. DOI:https://doi.org/10.15446/dyna.v85n207.71535.

ACS

(1)
Sereno, J. E.; Caicedo, M. A.; Rivadeneira, P. S. Artificial pancreas: glycemic control strategies for avoiding hypoglycemia. DYNA 2018, 85, 198-207.

APA

Sereno, J. E., Caicedo, M. A. & Rivadeneira, P. S. (2018). Artificial pancreas: glycemic control strategies for avoiding hypoglycemia. DYNA, 85(207), 198–207. https://doi.org/10.15446/dyna.v85n207.71535

ABNT

SERENO, J. E.; CAICEDO, M. A.; RIVADENEIRA, P. S. Artificial pancreas: glycemic control strategies for avoiding hypoglycemia. DYNA, [S. l.], v. 85, n. 207, p. 198–207, 2018. DOI: 10.15446/dyna.v85n207.71535. Disponível em: https://revistas.unal.edu.co/index.php/dyna/article/view/71535. Acesso em: 23 mar. 2026.

Chicago

Sereno, Juan E., Michelle A. Caicedo, y Pablo S. Rivadeneira. 2018. «Artificial pancreas: glycemic control strategies for avoiding hypoglycemia». DYNA 85 (207):198-207. https://doi.org/10.15446/dyna.v85n207.71535.

Harvard

Sereno, J. E., Caicedo, M. A. y Rivadeneira, P. S. (2018) «Artificial pancreas: glycemic control strategies for avoiding hypoglycemia», DYNA, 85(207), pp. 198–207. doi: 10.15446/dyna.v85n207.71535.

MLA

Sereno, J. E., M. A. Caicedo, y P. S. Rivadeneira. «Artificial pancreas: glycemic control strategies for avoiding hypoglycemia». DYNA, vol. 85, n.º 207, octubre de 2018, pp. 198-07, doi:10.15446/dyna.v85n207.71535.

Turabian

Sereno, Juan E., Michelle A. Caicedo, y Pablo S. Rivadeneira. «Artificial pancreas: glycemic control strategies for avoiding hypoglycemia». DYNA 85, no. 207 (octubre 1, 2018): 198–207. Accedido marzo 23, 2026. https://revistas.unal.edu.co/index.php/dyna/article/view/71535.

Vancouver

1.
Sereno JE, Caicedo MA, Rivadeneira PS. Artificial pancreas: glycemic control strategies for avoiding hypoglycemia. DYNA [Internet]. 1 de octubre de 2018 [citado 23 de marzo de 2026];85(207):198-207. Disponible en: https://revistas.unal.edu.co/index.php/dyna/article/view/71535

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CrossRef citations3

1. Ricardo Sanz, Iván Sala-Mira, Pedro García, José-Luis Díez, Jorge Bondia. (2024). Design of PD Controllers with Input Saturation for Postprandial Blood Glucose Regulation . IFAC-PapersOnLine, 58(7), p.198. https://doi.org/10.1016/j.ifacol.2024.08.034.

2. Amer B. Rakan, Taghreed M. Ridha, Shibly A. Al-Saamray. (2021). Automatic Glycemia Regulation: Avoiding Hypoglycemia and Hyperglycemia. 2021 International Conference on Communication & Information Technology (ICICT). , p.74. https://doi.org/10.1109/ICICT52195.2021.9568492.

3. Boubekeur Targui, Jose‐Fernando Castro‐Gomez, Omar Hernández‐González, Guillermo Valencia‐Palomo, María‐Eusebia Guerrero‐Sánchez. (2024). Observer‐based control for plasma glucose regulation in type 1 diabetes mellitus patients with unknown input delay. International Journal for Numerical Methods in Biomedical Engineering, 40(7) https://doi.org/10.1002/cnm.3826.

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