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While the Artificial Pancreas is effective in regulating the blood glucose inthe safe range of 70-180 mg/dl in type 1 diabetic patients, the highintra-patient variability, as well as exogenous meal disturbances, poses aserious challenge. The existing control algorithms thus require additionalsafety algorithms and feed-forward actions. Moreover, the unavailability ofinsulin sensors in Artificial Pancreas makes this task more difficult. In thepresent work, a subcutaneous model of type 1 diabetes (T1D) is considered forobserver-based controller design in the framework of contraction analysis. Avariety of realistic multiple-meal scenarios for three virtual T1D patientshave been investigated with +30 % and -30 % of parametric variability. Theaverage time spent by the three T1D patients is found to be 77 %, 73 % and 76%, respectively. A significant reduction in the time spent in hyperglycemia(>180 mg/dl) is achieved without any feed-forward action for meal compensation.

A contraction theory approach to observer-based controller design for glucose regulation in type 1 diabetes with intra-patient variability