Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach. Issue 5 (1st October 2018)

• Record Type: Journal Article
• Authors: Nath, Anirudh; Deb, Dipankar; Dey, Rajeeb; Das, Sipon
• Is Part Of: IET systems biology. Volume 12:Issue 5(2018)
• Page Start: 219
• Page End: 225
• Publication Date: 2018-10-01
• Subjects: patient monitoring -- adaptive control -- diseases -- Lyapunov methods -- closed loop systems -- medical control systems -- patient treatment -- medical computing -- sugar -- uncertain systems -- blood -- nonlinear control systems -- physiological models; blood glucose regulation -- type 1 diabetic patients -- adaptive parametric compensation control‐based approach -- direct adaptive control strategy -- nonlinear model -- type 1 diabetes mellitus patients -- uncertain parameters -- appropriate design -- adaptation laws -- closed‐loop response -- plasma glucose concentration -- external insulin infusion rate -- model parameters -- adaptive control scheme -- parametric uncertainty -- inter‐patient variability; Systems biology -- Periodicals; Cell physiology -- Periodicals; Biological systems -- Mathematical models -- Periodicals; Genetics -- Mathematical models -- Periodicals; Computational biology -- Periodicals; 573
• DOI: 10.1049/iet-syb.2017.0093
• Languages: English
• ISSNs: 1751-8849

Abstract

Abstract : Here, a direct adaptive control strategy with parametric compensation is adopted for an uncertain non‐linear model representing blood glucose regulation in type 1 diabetes mellitus patients. The uncertain parameters of the model are updated by appropriate design of adaptation laws using the Lyapunov method. The closed‐loop response of the plasma glucose concentration as well as external insulin infusion rate is analysed for a wide range of variation of the model parameters through extensive simulation studies. The result indicates that the proposed adaptive control scheme avoids severe hypoglycaemia and gives satisfactory performance under parametric uncertainty highlighting its ability to address the issue of inter‐patient variability.