Work

Multiple Constrained MPCs for glucose regulation in Type 1 Diabetes

Year: 2025

Type: article

Abstract: This study introduces a personalized Model Predictive Control (MPC) strategy for managing type 1 diabetes, specifically addressing intra-day variability in glucose regulation. The proposed method uses a soft-switching mechanism combining multiple MPCs, each optimized for distinct day periods (breakfast, lunch, and dinner). Patient-specific models were identified using an enhanced impulse response technique, featuring a novel clinically-based cost function to better capture circadian dynamics. A switching mechanism ensures smooth transitions between controllers, minimizing disruptions. Performance was evaluated using the FDA-approved UVA/Padova simulator, demonstrating a 20% improvement in model fit and enhanced control performance compared to the state-of-art approach. The strategy consistently prevented hypoglycemia while improving time-in-target metrics.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2025.06.006

Authors: Matteo Ragni, Paolo A. Mongini, Lalo Magni, Chiara Toffanin

Institution: University of Pavia

Language: English

Topic: Diabetes Management and Research

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

Funders: European Commission, Ministero dell’Istruzione, dell’Università e della Ricerca, Horizon 2020 Framework Programme