Artificial pancreas under stable pulsatile MPC: Improving the closed-loop performance

This work presents a pulsatile Zone Model Predictive Control (pZMPC) for the control of blood glucose concentration (BGC) in patients with Type 1 Diabetes Mellitus (T1DM). The main novelties of the algorithm – in contrast to other existing strategies – are: (i) it controls the patient glycemia by in...

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Autores principales: Abuin, Pablo, Rivadeneira, Pablo, Ferramosca, Antonio, González, Alejandro
Formato: Artículo publisherVersion
Lenguaje:Inglés
Publicado: 2021
Materias:
Pulsatile controlHybrid controlModel predictive controlArtificial pancreasInsulin functional therapyStability
Acceso en línea:http://hdl.handle.net/20.500.12272/4874
https://doi.org/10.1016/j.jprocont.2020.06.009
Aporte de:
RIA - Repositorio Institucional Abierto (UTN) de Universidad Tecnológica Nacional
id I68-R174-20.500.12272-4874
record_format dspace
institution Universidad Tecnológica Nacional
institution_str I-68
repository_str R-174
collection RIA - Repositorio Institucional Abierto (UTN)
language Inglés
topic Pulsatile controlHybrid controlModel predictive controlArtificial pancreasInsulin functional therapyStability
spellingShingle Pulsatile controlHybrid controlModel predictive controlArtificial pancreasInsulin functional therapyStability
Abuin, Pablo
Rivadeneira, Pablo
Ferramosca, Antonio
González, Alejandro
Artificial pancreas under stable pulsatile MPC: Improving the closed-loop performance
topic_facet Pulsatile controlHybrid controlModel predictive controlArtificial pancreasInsulin functional therapyStability
description This work presents a pulsatile Zone Model Predictive Control (pZMPC) for the control of blood glucose concentration (BGC) in patients with Type 1 Diabetes Mellitus (T1DM). The main novelties of the algorithm – in contrast to other existing strategies – are: (i) it controls the patient glycemia by injecting short duration insulin boluses for both, the basal and bolus infusions, in an unified manner, (ii) it performs the predictions and estimations (critical to anticipate both, hypo and hyperglycemia) based on a physiological individualized long-term model, (iii) it employs disturbance observers to compensate plant-model mismatches, (iv) it ensures, under standard assumptions, closed-loop stability, and (v) it can be used – under minor modifications – as an optimal basal–bolus calculator to emulate conventional therapies. Because of the latter characteristic, a significantly better performance is achieved, not only in terms of classical indexes (time in the normoglycemia zone, avoidance of hypoglycemia in the short term, avoidance of hyperglycemia in the long term) but also in terms of its applicability (use of the pump or injections). Such a performance is tested in a cohort of in-silico patients from the FDA-accepted UVA/Padova simulation platform, considering the most challenging scenarios.
format Artículo
publisherVersion
author Abuin, Pablo
Rivadeneira, Pablo
Ferramosca, Antonio
González, Alejandro
author_facet Abuin, Pablo
Rivadeneira, Pablo
Ferramosca, Antonio
González, Alejandro
author_sort Abuin, Pablo
title Artificial pancreas under stable pulsatile MPC: Improving the closed-loop performance
title_short Artificial pancreas under stable pulsatile MPC: Improving the closed-loop performance
title_full Artificial pancreas under stable pulsatile MPC: Improving the closed-loop performance
title_fullStr Artificial pancreas under stable pulsatile MPC: Improving the closed-loop performance
title_full_unstemmed Artificial pancreas under stable pulsatile MPC: Improving the closed-loop performance
title_sort artificial pancreas under stable pulsatile mpc: improving the closed-loop performance
publishDate 2021
url http://hdl.handle.net/20.500.12272/4874
https://doi.org/10.1016/j.jprocont.2020.06.009
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