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Variable structure-based controllers applied to the modified Hovorka model for type 1 diabetes

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Abstract

Despite the fact that diabetes treatment technology is constantly evolving, research groups continue to highlight the problem of blood glucose concentration management as a critical concern. Uncontrolled blood glucose levels in the body can result from pancreas failure. The majority of diabetic patients are unable to maintain an optimal glucose concentration level and effective control is required to improve diabetic treatment. In the formulation of a control algorithm for an artificial pancreas, the modified Hovorka model was recently introduced to further explain the glucose-insulin dynamics. In this research paper, different control strategies have been implemented and compared: sliding mode control, integral and double integral sliding mode control and proportional integral derivative control used as a baseline. The goal is the evaluation of nonlinear controllers using Lyapunov theory, applied to a biologically relevant nonlinear complex model able to describe the interaction between blood glucose and insulin, based on the Hovorka equations. The proposed controllers have to achieve the desired reference level of stability and robustness in glucose concentration regulation. The key performance indexes adopted are chattering, settling time and steady-state error, also considering computational complexities. A genetic algorithm has also been adopted for parameter optimization to improve each controller’s performance. The effect of perturbations in the form of food consumption was also analyzed and compared for the different control strategies.

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Data availability

Simulation data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

GC:

Glucose concentration

CGM:

Continuous glucose monitoring

APs:

Artificial pancreas

GA:

Genetic algorithm

MHo:

Modified Hovorka model

MPC:

Model predictive control

SMC:

Sliding mode control

ISMC:

Integral SMC

DISMC:

Double ISMC

ITAE:

Integral of absolute magnitude of the error

IAE:

Integral of absolute error

FLOP:

Floating point operations

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The authors did not receive support from any organization for the submitted work.

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Author notes

  1. I. S. Mughal, L. Patanè, M. G. Xibilia and R. Caponetto have contributed equally to this work.

Authors and Affiliations

  1. Dipartimento di Ingegneria, Elettrica, Elettronica e Informatica - DIEEI, University of Catania, Viale Andrea Doria, 6, 95125, Catania, Italy

    Iqra Shafeeq Mughal

  2. Department of Engineering, University of Messina, Contrada di Dio, S. Agata, 98166, Messina, Italy

    Luca Patanè, Maria Gabriella Xibilia & Riccardo Caponetto

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  1. Iqra Shafeeq Mughal
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  2. Luca Patanè
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Correspondence to Riccardo Caponetto.

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Mughal, I.S., Patanè, L., Xibilia, M.G. et al. Variable structure-based controllers applied to the modified Hovorka model for type 1 diabetes. Int. J. Dynam. Control 11, 3159–3175 (2023). https://doi.org/10.1007/s40435-023-01150-4

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