Abstract
This article investigates the blood glucose regulation problem of type 1 diabetes patients embedded with an artificial pancreas based on an adaptive event-triggered mechanism. The blood glucose regulation system with parameter uncertainties is modeled by an uncertain Takagi–Sugeno (T–S) fuzzy system and a robust H∞ controller is designed to drive the artificial pancreas to regulate the insulin infusion. The releasing of feedback control signals is determined via an adaptive event-triggered mechanism. In this mechanism, a dynamic triggering threshold can be regulated adaptively according to the system dynamics. Particularly, when the blood glucose of patients is increased by eating some meals, the triggering threshold will be reduced to transmit more signals to maintain the glucose in a safe level. Without requiring all Lyapunov matrices to be positive, new less conservative conditions for ensuring the H∞ stability of closed-loop fuzzy systems are obtained by linear matrix inequalities (LMIs). Then, a co-designed strategy is presented to derive the controller gains and the triggering matrix simultaneously. The effectiveness of the developed approach is shown by some simulation results.
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