Insulin drug regulation by general type 2 fuzzy controller with alpha plane

Insulin therapy with an insulin pump for diabetic patients has different challenges in the real world. Physiological uncertainties in human bodies, different types of daily activities are the most important challenges in this field. Besides, delay in CHO effects in blood glucose may increase the risk of hypoglycemic and hyperglycemic. In this paper, general type 2 fuzzy controller with alpha-plane has been used to handle the uncertainties and a neural network predictor to estimate the blood glucose in next hour as well. Genetic algorithm is also used to tune some free parameters in the controller. in addition, Fuzzy rules have been weighted by predefined values based on the prediction of the amount of glucose in one hour late. in such case, rule weighting has been adjusted according to the glucose of the body which in turn two high risk situations of diabetic patients (hyperglycemia and hypoglycemia) have been considered in fuzzy inference. the Simulation results on Hovorka model shows that the controller can regulate the blood glucose in the existence of uncertainty in model and CHO regimen without the risk of hypoglycemic and hyperglycemic situations.