Type 3 Fuzzy Predictive Control of the Insulin-Glucose System in Type 1 Diabetes

In this article, a predictive controller using a type 3 fuzzy system is presented to regulate blood glucose levels in type 1 diabetic patients. Using type 3 fuzzy systems leads to higher accuracy in dealing with uncertainty. The glucose in the dynamics of type 1 diabetes is supposed to be unknown, and it is estimated online by the type 3 fuzzy system. The control system consists of a predictive controller and an adaptive compensation structure. The predictive controller is designed by defining the cost function based on the steady-state value of the control signal using the output information of the fuzzy system. Also, the Lyapunov stability analysis is used to design a compensator to ensure the stability of the closed-loop system. The proposed methodology is examined on the minimal Bergman model for different patients under parametric uncertainty, noise, and disturbance. And also, the proposed method is compared with other well-known methods.