Neural adaptive control of an artificial pancreas for people with type 1 diabetes under saturated insulin injection rate

It is essential to control vital variables in patients whose natural control system has been compromised for some reason. One of these vital variables is blood glucose levels. Unfortunately, in people with diabetes (blood sugar), blood glucose levels are not regulated properly. To compensate for this lack, in recent years, several studies and efforts have been made to build and improve the function of the artificial pancreas to control blood sugar. The presence of factors such as multiple uncertainties due to physiological differences in individuals, various activities during the day, delayed effects of carbohydrates on blood sugar levels, stress and exercise make controlling the artificial pancreas a challenging system. But one of the most important challenges in this area, which has not been less addressed in the literature is the limitation on the allowable dose of insulin injected into the artificial pancreas for patients with type 1 diabetes. On the one hand, injecting a high dose of insulin can cause problems such as hyperglycemia issues and on the other hand, injecting a negative dose of insulin is meaningless. In this paper, after selecting the Bergman model and considering the existence of asymmetric saturation in the actuator, the back-stepping control method is used and it is combined with an adaptive technique to improve the controller performance. Finally, simulation results depict that in the presence of large step disturbance, the insulation rate remains in the allowed band of zero to 20 mU/min, and the blood glucose level does not exceed the appropriate level 130mg/dl.