An augmented subcutaneous type 1 diabetic patient modelling and design of adaptive glucose control. (February 2020)

• Record Type: Journal Article
• Authors: Nath, Anirudh; Deb, Dipankar; Dey, Rajeeb
• Is Part Of: Journal of process control. Volume 86(2020)
• Page Start: 94
• Page End: 105
• Publication Date: 2020-02
• Subjects: Artificial pancreas -- Adaptive control -- Type 1 diabetes -- Intra-patient variability -- Parameter estimation; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2019.08.010
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: A simplified control-oriented nonlinear subcutaneous glucose-insulin models for Type 1 diabetes have been proposed. Parameter estimation of the proposed model is done using the data of a more complicated nonlinear model using the nonlinear least squares method. A nonlinear adaptive controller is proposed that makes the uncertain system to follow a reference system. The proposed adaptive controller provided an improved post-prandial glycemic control under intra-patient variability. Abstract: In the present work, an augmented subcutaneous (SC) model of type 1 diabetic patients (T1DP) is proposed first by estimating the model parameters with the aid of nonlinear least square method using the physiological data. Next, a nonlinear adaptive controller is proposed to tackle two important issues of intra-patient variability (IPV) and uncertain meal disturbance (MD). The proposed patient model agrees quite well with the responses of one of the most popular existing nonlinear model used in the research of artificial pancreas. Further, the developed adaptive control is shown to be capable of providing desired glycemic control without feed-forward action for meal compensation or safety algorithms to avoid hypoglycemia. Due to the simple structure and capability of handling intra-patient variability of the adaptive controller, it can find immediate applicability in the development of the in-silico artificial pancreas.