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Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach

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...

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Autores principales: Nath, Anirudh, Deb, Dipankar, Dey, Rajeeb, Das, Sipon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Institution of Engineering and Technology 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687408/
https://www.ncbi.nlm.nih.gov/pubmed/30259867
http://dx.doi.org/10.1049/iet-syb.2017.0093
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author Nath, Anirudh
Deb, Dipankar
Dey, Rajeeb
Das, Sipon
author_facet Nath, Anirudh
Deb, Dipankar
Dey, Rajeeb
Das, Sipon
author_sort Nath, Anirudh
collection PubMed
description 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.
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spelling pubmed-86874082022-02-16 Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach Nath, Anirudh Deb, Dipankar Dey, Rajeeb Das, Sipon IET Syst Biol Research Article 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. The Institution of Engineering and Technology 2018-10-01 /pmc/articles/PMC8687408/ /pubmed/30259867 http://dx.doi.org/10.1049/iet-syb.2017.0093 Text en © 2020 The Institution of Engineering and Technology https://creativecommons.org/licenses/by/3.0/This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/ (https://creativecommons.org/licenses/by/3.0/) )
spellingShingle Research Article
Nath, Anirudh
Deb, Dipankar
Dey, Rajeeb
Das, Sipon
Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach
title Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach
title_full Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach
title_fullStr Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach
title_full_unstemmed Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach
title_short Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach
title_sort blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687408/
https://www.ncbi.nlm.nih.gov/pubmed/30259867
http://dx.doi.org/10.1049/iet-syb.2017.0093
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