Abstract
Artificial Pancreas (AP) will help large diabetic patients to manage their disease. This paper presents a new Control Algorithm used in AP. This algorithm is based on a model predictive control and characterized by an acceleration of control law without producing overshoot. The method consists on the introduction of two penalization function in the cost function according to the system dynamic. Simulations under a realistic scenario in approved platform of simulation demonstrate the success of this method to obtain satisfactory control performances.
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Abbreviations
- AP:
-
artificial pancreas
- MPC:
-
model predictive control
- T1DM:
-
Type 1 diabetes mellitus
- BG:
-
blood glucose
- z-MPC:
-
zone-MPC
- e-MPC:
-
enhanced-MPC
- CHO:
-
carbohydrates
- CGM:
-
continuous glucose monitor
- CSII:
-
continuous subcutaneous insulin injection
- FDA:
-
Food and Drug Administration
- TDI:
-
total daily insulin
- mg/dL:
-
milligrams per deciliter N
- pmol/min:
-
picomoles per minute
- UVA/Padova:
-
Universities of Virginia/Padova
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Acknowledgements
This work returns the framework of the research project SISA1 “Mini intelligent Power plant” began between research center SISA and our University. We are anxious to think the Hassan II University of Casablanca for the financing of this project.
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El Hachimi, M., Ballouk, A., Baghdad, A. (2019). Rapid Model Predictive Controller for Artificial Pancreas. In: El Hani, S., Essaaidi, M. (eds) Recent Advances in Electrical and Information Technologies for Sustainable Development. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-05276-8_8
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DOI: https://doi.org/10.1007/978-3-030-05276-8_8
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