Predictive Active Disturbance Rejection Control for Insulin Infusion in Patients with T1DM

This paper presents an active disturbance rejection control scheme to automatically regulate the glucose level in type 1 diabetic patients. Although the blood glucose system is nonlinear, in this control approach, it is represented as a linear perturbed system, whose lumped disturbance input is estimated by an Extended State Observer (ESO) and then compensated by an robust controller tuned with Quantitative Feedback Theory (QFT). The robust control scheme uses a Smith predictor for the time delay compensation and allows taking into account the inter-patient variability presented in the glucose control problem. In order to validate the effectiveness of this approach, the controller is tested in silico on a cohort of adult patients of the UVA/Padova metabolic simulator, which has been accepted by the Food and Drug Administration (FDA). In silico results indicate that safe blood glucose control can be achieved by the proposed controller.