Constrained Linear Model Predictive Control for an Artificial Pancreas

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Tarih

2024

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Yayıncı

Institute of Electrical and Electronics Engineers Inc.

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

The achievement of closed-loop glycemic control, and hence the automation of insulin administration, is highly required in the implementation of an Artificial Pancreas system. Various control theory approaches have been employed in numerous attempts to design an appropriate control algorithm. In our study, we adopted a Constrained linear model predictive controller (CLMPC). Our simulations have shown that the Constrained LMPC algorithm performs exceptionally well in maintaining blood glucose levels for patients across different scenarios. It effectively manages measurement and process noise, which is crucial for the practical implementation of the system. Moreover, the incorporation of feedforward capability in the controller has shown significant benefits, enabling proactive planning for future meals and optimizing blood glucose levels. Our CLMPC is more effective and very simple than the one presented in the literature, making it suitable for simple smartphone applications that support diabetes self-management. © 2024 IEEE.

Açıklama

8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024 -- 21 April 2024 through 22 April 2024 -- Biskra -- 199870

Anahtar Kelimeler

Artificial Pancreas; Automatic Insulin Delivery; Closed-loop system; Control Algorithm; Model Predictive Control

Kaynak

Proceedings - 8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024

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