A Glucose Control Approach for Type-1 Diabetes via Takagi-Sugeno Fuzzy Models

The problem of controlling the blood glucose level for type-1 diabetes is considered in this paper. The nonlinear dynamics that quantifying insulin sensitivity and glucose effectiveness for type-1 diabetes are extended to incorporate free fatty acid (FFA) dynamics, which are then explained in the Takagi-Sugeno (T-S) fuzzy model. The proposed T-S fuzzy control method is derived based on quadratic Lyapunov function and parallel distributed compensation (PDC) which aim at adjusting the blood glucose level as well as free fatty acid level in a normal sense. Conditions for the solvability of the controller design are expressed as the form of linear matrix inequalities. Further, convex optimization techniques are used for deriving linear matrix inequalities. To verify the validity and applicability of the proposed approach, simulation examples are given in the end of the paper.