Survey on diabetes is one of the popular fields of biomedical signal processing. In this paper, a closed-loop system which utilizes modified Stolwijk-Hardy glucose insulin interaction model is considered. The modified model was derived by adding an exogenous insulin infusion term. Two control algorithms are used for exogenous insulin infusion: a Mamdani type fuzzy logic controller (FLC), and a fuzzy-PID controller. Simulations are performed to assess control function in terms of keeping desired steady state plasma glucose level (0.81 mg/ml) against to exogenous glucose input. Simulation results are notable and significant in terms of controlling blood glucose level (BGL). The control algorithms that applied to the model are firstly proposed, therefore this study is made a contribution to the literature.

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-Type 1 Diabetes Mellitus (T1DM) is a worldwide disease. Although a complete cure has not been found yet, an artificial pancreas (AP), also known as a closed-loop insulin therapy, is becoming more important for the treatment of this disease. Controller part of the AP can compute insulin infusion rate that will keep blood glucose concentration (BGC) in normoglycemic ranges for patients with T1DM. In this paper, three different control algorithms are proposed as a controller part of the AP. These control algorithms include genetic algorithm based proportional-integral-derivative (GA-PID) control, artificial bee colony algorithm based PID (ABC-PID) control, and particle swarm optimization algorithm based PID (PSO-PID) control. In silico control studies are implemented through a virtual diabetic patient based on the Stolwijk-Hardy's glucose-insulin regulation model. Simulations are performed to assess control function in terms of tracking BGC profile of a healthy person against to a daily food intake of three meals. In order to demonstrate robustness, sensor noise test is implemented. Simulation results are promising in terms of regulating the daily BGC.

In this paper, a Mamdani-type fuzzy controller is proposed as the controller part of an artificial pancreas. The controller is optimized with the artificial bee colony optimization algorithm. The glucose-insulin regulatory system, based on a nonlinear differential model in the presence of delay, is used both for virtual patient and healthy person data. The main target of the controller is to mimic a blood glucose concentration profile of the healthy person with exogenous insulin infusion. Simulations are performed to assess the control function in terms of tracking the blood glucose concentration profile of the healthy person and minimizing errors. To show robustness, a group of three tests are implemented. These tests include unusual glucose intake, sensor noise, and uncertainty in the clearance rate parameter. The simulation results demonstrate that the adopted method is more effective than similar studies in the literature.