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Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus

Cifha Crecil Dias, Surekha Kamath, Sudha Vidyasagar

2020IET Systems Biology17 citationsDOIOpen Access PDF

Abstract

This study elaborates on the design of artificial pancreas using model predictive control algorithm for a comprehensive physiological model such as the Sorensen model, which regulates the blood glucose and can have a longer control time in normal glycaemic region. The main objective of the proposed algorithm is to eliminate the risk of hyper and hypoglycaemia and have a precise infusion of hormones: insulin and glucagon. A single model predictive controller is developed to control the bihormones, insulin, and glucagon for such a development unmeasured disturbance is considered for a random time. The simulation result for the proposed algorithm performed good regulation lowering the hypoglycaemia risk and maintaining the glucose level within the normal glycaemic range. To validate the performance of the tracking of output and setpoint, average tracking error is used and 4.4 mg/dl results are obtained while compared with standard value (14.3 mg/dl).

Topics & Concepts

SetpointArtificial pancreasGlucagonModel predictive controlInsulinDiabetes mellitusInternal medicineController (irrigation)EndocrinologyControl theory (sociology)MedicineType 1 diabetesHypoglycemiaBlood sugar regulationTracking errorPredictive valueComputer scienceControl (management)BiologyArtificial intelligenceAgronomyDiabetes Management and ResearchPancreatic function and diabetesDiabetes and associated disorders
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