PREDICTIVE CONTROL OF BLOOD GLUCOSE CONCENTRATION IN TYPE-I DIABETIC PATIENTS USING LINEAR INPUT-OUTPUT MODELS

Intra- and inter-patient variability poses a challenging task to control blood glucose concentration in diabetic patients. A data based model predictive control with state and disturbance estimation has been developed to control the blood glucose concentration in the type-I diabetic patients in the presence of meal disturbances under patient-model mismatch. Simulation studies were performed on three distinct patient models generated as a result of sensitivity analysis, which revealed that the proposed control strategy is able to control the blood glucose concentration well within the acceptable limits and also able to compensate for the slow parametric drifts.