基于胰岛素基础率估计的人工胰腺系统自抗扰控制

Insulin basal rate provides the reference for closed-loop blood glucose regulation using artificial pancreas systems, but this quantity is usually difficult to determine accurately in clinical practice. In this regard, this paper introduces an active disturbance rejection control method for artificial pancreas systems based on dynamic estimation of the basal rate. To enable improved glucose regulation, an extended state observer (ESO) is employed to estimate the internal and external disturbances in the glucose metabolic process, and a feedback control law and insulin infusion safety constraints that both incorporate parameter adaptation are proposed. Based on the proposed method, an artificial pancreas software system is designed for mobile devices with Bluetooth modules. The proposed results are evaluated through comparative simulations and functionality tests by using the US FDA (Food and Drug Administration)-accepted UVA/Padova T1DM simulator. The obtained results provide methodological and technical support for further clinical studies of artificial pancreas systems, and introduce a precision medicine solution to enhanced glucose management for Chinese patients with diabetes mellitus.