Design of an online-tuned model based compound controller for a fully automated artificial pancreas

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...

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Main Authors: Bhattacharjee, Arpita, Easwaran, Arvind, Leow, Melvin Khee-Shing, Cho, Nam-Joon
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/152798
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1527982021-10-01T05:11:13Z Design of an online-tuned model based compound controller for a fully automated artificial pancreas Bhattacharjee, Arpita Easwaran, Arvind Leow, Melvin Khee-Shing Cho, Nam-Joon School of Computer Science and Engineering Lee Kong Chian School of Medicine (LKCMedicine) School of Materials Science and Engineering Science::Medicine Science::Biological sciences Type 1 Diabetes Mellitus Artificial Pancreas 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. s The authors wish to thank their funding source, NTU-NHG Ageing Research Grant: ARG/14015. 2021-10-01T05:11:13Z 2021-10-01T05:11:13Z 2019 Journal Article 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 0140-0118 https://hdl.handle.net/10356/152798 10.1007/s11517-019-01972-5 30895514 2-s2.0-85063196584 7 57 1437 1449 en ARG/14015 Medical & biological engineering & computing ©2019 International Federation for Medical and Biological Engineering. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Medicine
Science::Biological sciences
Type 1 Diabetes Mellitus
Artificial Pancreas
spellingShingle Science::Medicine
Science::Biological sciences
Type 1 Diabetes Mellitus
Artificial Pancreas
Bhattacharjee, Arpita
Easwaran, Arvind
Leow, Melvin Khee-Shing
Cho, Nam-Joon
Design of an online-tuned model based compound controller for a fully automated artificial pancreas
description 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.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Bhattacharjee, Arpita
Easwaran, Arvind
Leow, Melvin Khee-Shing
Cho, Nam-Joon
format Article
author Bhattacharjee, Arpita
Easwaran, Arvind
Leow, Melvin Khee-Shing
Cho, Nam-Joon
author_sort Bhattacharjee, Arpita
title Design of an online-tuned model based compound controller for a fully automated artificial pancreas
title_short Design of an online-tuned model based compound controller for a fully automated artificial pancreas
title_full Design of an online-tuned model based compound controller for a fully automated artificial pancreas
title_fullStr Design of an online-tuned model based compound controller for a fully automated artificial pancreas
title_full_unstemmed Design of an online-tuned model based compound controller for a fully automated artificial pancreas
title_sort design of an online-tuned model based compound controller for a fully automated artificial pancreas
publishDate 2021
url https://hdl.handle.net/10356/152798
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