Fuzzy-Genetic Control of Blood Glucose Level in Diabetic Patients Based on Palumbo Delayed Model

Diabetes is one of the important issues in the medical field in which blood glucose level control and regulation needs to permanent care. Determination of appropriate rate of insulin injection in order to blood glucose level stabilization to a normal level is vital for diabetics. In this paper, optimal plasma blood glucose tracking using subcutaneous insulin administration is investigated. Here one of the recent mathematical models is used for glucose-insulin regulatory system which consists of delayed nonlinear differential equations that is one of the most comprehensive models in this field, known as Palumbo. In this paper for the first time, the optimal fuzzy logic controller method with genetic algorithm based on the Palumbo mathematical model is used to regulate blood glucose level in diabetic patients. One of the most important features of the proposed controller is the ability to set the parameters for patients using genetic algorithm. Finally, the simulation results of the fuzzy control method and fuzzy- genetic control method are compared with the control method based on Palumbo feedback linearization, which indicates the proper functioning of the proposed controller for tracking of desired blood glucose level at the lowest possible error.

Keywords:

Fuzzy logic method , Genetic algorithm , Glucose-Insulin regulation system , Insulin injection , Palumbo delayed nonlinear model