An Optimized Model-Reference Blood Glucose Adaptive Control for Type 1 Diabetes

This article proposes the design and implementation of an optimized adaptive controller for an artificial pancreas, aimed at managing the human glycemic system. Using an identified model of the human glucose metabolic system, the adaptive control strategy is developed to dynamically adjust to the individual variations in the metabolic processes, providing a personalized approach to glucose regulation. Simulation results demonstrate the high performance of the proposed control strategy comparatively to an optimized PID controller. The results highlight the potential of adaptive control systems in improving the management of diabetes through automated and individualized insulin delivery.