Type 1 diabetes mellitus is a disorder characterized by elevated blood glucose levels resulting from inadequate or missing insulin synthesis. To regulate glycemia, diabetic patients require exogenous insulin infusion. This paper presents a comparison of four control strategies for autonomous regulation of glycemia, i.e., integer and fractional order variations of proportional integral control and sliding mode control. Genetic algorithms are employed for optimizing glycemic regulation, that are validated through numerical simulations on the fractional Bergman glucoregulatory model in presence of meal disturbance. It is found that the fractional version of the sliding mode controller exhibits superior performance in terms in time in normal glycemic range and time spent in hypoglycemia, also showing robustness properties with respect to meal increments.

Fractional Order Modeling and Control of Type 1 Diabetes with Genetic Algorithm Optimization / Caponetto, Riccardo; Patanè, Luca; Koledin, Nebojša; Wrona, Andrea; Baldisseri, Federico; Delli Priscoli, Francesco. - (2025), pp. 808-813. (Intervento presentato al convegno 2025 IEEE 21st International Conference on Automation Science and Engineering tenutosi a Los Angeles) [10.1109/case58245.2025.11164067].

Fractional Order Modeling and Control of Type 1 Diabetes with Genetic Algorithm Optimization

Wrona, Andrea
Methodology
;
Baldisseri, Federico;Delli Priscoli, Francesco
Supervision
2025

Abstract

Type 1 diabetes mellitus is a disorder characterized by elevated blood glucose levels resulting from inadequate or missing insulin synthesis. To regulate glycemia, diabetic patients require exogenous insulin infusion. This paper presents a comparison of four control strategies for autonomous regulation of glycemia, i.e., integer and fractional order variations of proportional integral control and sliding mode control. Genetic algorithms are employed for optimizing glycemic regulation, that are validated through numerical simulations on the fractional Bergman glucoregulatory model in presence of meal disturbance. It is found that the fractional version of the sliding mode controller exhibits superior performance in terms in time in normal glycemic range and time spent in hypoglycemia, also showing robustness properties with respect to meal increments.
2025
2025 IEEE 21st International Conference on Automation Science and Engineering
Fractional order Control; Fractional order modeling; Genetic Algorithm; Diabetes; PI; SMC.
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Fractional Order Modeling and Control of Type 1 Diabetes with Genetic Algorithm Optimization / Caponetto, Riccardo; Patanè, Luca; Koledin, Nebojša; Wrona, Andrea; Baldisseri, Federico; Delli Priscoli, Francesco. - (2025), pp. 808-813. (Intervento presentato al convegno 2025 IEEE 21st International Conference on Automation Science and Engineering tenutosi a Los Angeles) [10.1109/case58245.2025.11164067].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1748888
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