Bi-hormonal Linear Time-Varying Model Predictive Control for Blood Glucose Regulation in Type 1 Diabetes Patients

Conference Paper (2023)
Author(s)

Dylan Kalisvaart (TU Delft - Mechanical Engineering)

Jorge Bonekamp (Student TU Delft)

Sergio Grammatico (TU Delft - Mechanical Engineering, TU Delft - Mechanical Engineering)

Research Group
Team Carlas Smith
DOI related publication
https://doi.org/10.1109/CCTA54093.2023.10252997 Final published version
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Publication Year
2023
Language
English
Research Group
Team Carlas Smith
Pages (from-to)
552-558
ISBN (electronic)
979-8-3503-3544-6
Event
2023 IEEE Conference on Control Technology and Applications, CCTA 2023 (2023-08-16 - 2023-08-18), Bridgetown, Barbados
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Abstract

We study predictive control for blood glucose regulation in patients with type 1 diabetes mellitus. We determine optimal control actions for insulin and glucagon infusion via linear time-varying model predictive control (LTV MPC) and dynamic linerization around the state trajectory predicted. Through in silico implementation of a comprehensive nonlinear model, we show that our proposed controller is able to reject meal disturbances, retain normoglycemia afterwards and significantly outperform standard linearized MPC.

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