Blood Glucose Regulation in Patients with Type 1 Diabetes Mellitus: A Robust MRAC Approach

Roberto Franco, Hector Rios, Alejandra Ferreira De Loza, Denis Efimov, Louis Cassany, David Gucik-Derigny, Jerome Cieslak, David Henry

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper deals with the problem of robust blood glucose regulation in critically ill patients affected by type 1 diabetes mellitus. The blood glucose measurement and insulin infusion are intravenous. The proposed algorithm regulates blood glucose and keeps it in the normoglycemia range, i.e., 70-180 mg/dl. To this aim, a control law is proposed based on a Nonlinear Model Reference Adaptive Control approach. The algorithm is composed of nonlinear adaptive gains that ensure convergence to zero of the regulation error. The approach is validated in the UVA/Padova metabolic simulator for ten in silico adult patients with unannounced meals. The results perform well and have minimal risk of hyperglycemic and hypoglycemic events.

Original languageEnglish
Title of host publication60th IEEE Conference on Decision and Control, CDC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages661-666
Number of pages6
ISBN (Electronic)9781665436595
DOIs
StatePublished - 2021
Event60th IEEE Conference on Decision and Control, CDC 2021 - Austin, United States
Duration: 13 Dec 202117 Dec 2021

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2021-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference60th IEEE Conference on Decision and Control, CDC 2021
Country/TerritoryUnited States
CityAustin
Period13/12/2117/12/21

Keywords

  • Adaptive Control
  • Blood Glucose Regulation
  • Diabetes Mellitus Type 1

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