Feedforward-feedback multiple predictive controllers for glucose regulation in type 1 diabetes

Type 1 diabetic patients depend on insulin therapy to maintain blood glucose levels within safe range. The idea behind the " Artificial Pancreas" is to mimic, as close as possible, the functions of the natural pancreas in glucose sensing and insulin delivery, by using closed-loop control techniques. This work presents a model-based predictive control strategy for blood glucose regulation in diabetic patients. The controller is provided with a feedforward loop to improve meal compensation, a gain scheduling scheme to improve the controller performance in controlling the nonlinear glucose-insulin system, and an asymmetric cost function to reduce the hypoglycemic risk. Simulation scenarios with virtual patients are used to test the designed controller. The obtained results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against measurements errors, meal estimation errors, and changes in insulin sensitivity.