Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152798
Title: Design of an online-tuned model based compound controller for a fully automated artificial pancreas
Authors: Bhattacharjee, Arpita
Easwaran, Arvind
Leow, Melvin Khee-Shing
Cho, Nam-Joon
Keywords: Science::Medicine
Science::Biological sciences
Issue Date: 2019
Source: Bhattacharjee, A., Easwaran, A., Leow, M. K. & Cho, N. (2019). Design of an online-tuned model based compound controller for a fully automated artificial pancreas. Medical & Biological Engineering & Computing, 57(7), 1437-1449. https://dx.doi.org/10.1007/s11517-019-01972-5
Project: ARG/14015
Journal: Medical & biological engineering & computing
Abstract: This paper deals with the development of a control algorithm that can predict optimal insulin doses without patients' intervention in fully automated artificial pancreas system. An online-tuned model based compound controller comprising an online-tuned internal model control (IMC) algorithm and an enhanced IMC (eIMC) algorithm along with a meal detection module is proposed. Volterra models, used to develop IMC and eIMC algorithms, are developed online using recursive least squares (RLS) filter. The time domain kernels, computed online using RLS filter, are converted into frequency domain to obtain Volterra transfer function (VTF). VTFs are used to develop both IMC and eIMC algorithms. The compound controller is designed in such a way that eIMC predicts insulin doses when the glucose rate increase detector of meal detection module is positive, otherwise conventional IMC takes the control action. Experimental results show that the compound controller performs robustly in the presence of higher and irregular amounts of meal disturbances at random times, very high actuator and sensor noises and also with the variation in insulin sensitivity. The combination of compound control strategy and meal detection module compensates the shortcomings of both slow subcutaneous insulin action that causes postprandial hyperglycemia, and delayed peak of action that causes hypoglycaemia. Graphical Abstract A fully-automated artificial pancreas system containing glucose sensor, insulin pump and control algorithm. Block diagram showing the control algorithm i.e., online-tuned compound IMC comprising enhanced IMC, conventional IMC and meal detection module, developed in the present work.
URI: https://hdl.handle.net/10356/152798
ISSN: 0140-0118
DOI: 10.1007/s11517-019-01972-5
Rights: ©2019 International Federation for Medical and Biological Engineering. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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