Adaptive multivariable closed-loop control of blood glucose concentration in patients with Type 1 Diabetes

Abstract

Closed-loop control of blood glucose concentration is an alternative treatment for Diabetes patients by automatically controlling their blood glucose level. Recursive time-series models are found to be powerful tool for prediction and control of glucose concentration. However, the stability of such models cannot be guaranteed by regular identification methods. In this paper, we use a constrained optimization method for stability of models. Generalized predictive controller (GPC) is used to close the loop. Physiological signals are used and a multivariable model is created that also includes insulin on-board information to prevent hypoglycemia events. Seven experiments with 3 different patients are done. Results show GPC with constrained identification method and physiological signals can regulate blood glucose concentration successfully.