Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients

In this paper, chaotic dynamic and nonlinear control in a glucose-insulin system in types I diabetic patients and a healthy person have been investigated. Chaotic analysis methods of the blood glucose system include Lyapunov exponent and power spectral density based on the time series derived from t...

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Main Authors: Saeid Khajehvand, Seyed Mahdi Abtahi
Format: Article
Language:English
Published: Science and Research Branch,Islamic Azad University 2019-05-01
Series:Journal of Advances in Computer Engineering and Technology
Subjects:
Online Access:http://jacet.srbiau.ac.ir/article_13972_eff2c18ce90e4863fe9d27142d78f6ca.pdf
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spelling doaj-19035922345a40aeb195bce332c934622020-11-24T21:19:01ZengScience and Research Branch,Islamic Azad UniversityJournal of Advances in Computer Engineering and Technology2423-41922423-42062019-05-0152819213972Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patientsSaeid Khajehvand0Seyed Mahdi Abtahi1MS.C Student, Faculty of Electrical, Biomedical and Mechatronics Engineering, Qazvin branch, Islamic Azad University, Qazvin, IranAssistant Professor, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IranIn this paper, chaotic dynamic and nonlinear control in a glucose-insulin system in types I diabetic patients and a healthy person have been investigated. Chaotic analysis methods of the blood glucose system include Lyapunov exponent and power spectral density based on the time series derived from the clinical data. Wolf's algorithm is used to calculate the Lyapunov exponent, which positive values of the Lyapunov exponent mean the dynamical system is chaotic. Also, a wide range in frequency spectrum based on the power spectral density is also used to confirm the chaotic behavior. In order to control the chaotic system and reach the desired level of a healthy person's glucose, a novel fuzzy high-order sliding mode control method has been proposed. Thus, in the control algorithm of the high-order sliding mode controller, all of the control gains computed by the fuzzy inference system accurately. Then the novel control algorithm is applied to the Bergman's mathematical model that is verified using the clinical data set. In this system, the control input is the amount of insulin injected into the body and the control output is the amount of blood glucose level at any moment. The simulation results of the closed-loop system in various conditions, along with the performance of the control system in disturbance presence, indicate the proper functioning of this controller at the settling time, overshoot and the control inputs.http://jacet.srbiau.ac.ir/article_13972_eff2c18ce90e4863fe9d27142d78f6ca.pdfchaosglucose-insulin blood systemlyapunov exponentsliding mode controllerfuzzy logic
collection DOAJ
language English
format Article
sources DOAJ
author Saeid Khajehvand
Seyed Mahdi Abtahi
spellingShingle Saeid Khajehvand
Seyed Mahdi Abtahi
Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
Journal of Advances in Computer Engineering and Technology
chaos
glucose-insulin blood system
lyapunov exponent
sliding mode controller
fuzzy logic
author_facet Saeid Khajehvand
Seyed Mahdi Abtahi
author_sort Saeid Khajehvand
title Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
title_short Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
title_full Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
title_fullStr Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
title_full_unstemmed Chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
title_sort chaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
publisher Science and Research Branch,Islamic Azad University
series Journal of Advances in Computer Engineering and Technology
issn 2423-4192
2423-4206
publishDate 2019-05-01
description In this paper, chaotic dynamic and nonlinear control in a glucose-insulin system in types I diabetic patients and a healthy person have been investigated. Chaotic analysis methods of the blood glucose system include Lyapunov exponent and power spectral density based on the time series derived from the clinical data. Wolf's algorithm is used to calculate the Lyapunov exponent, which positive values of the Lyapunov exponent mean the dynamical system is chaotic. Also, a wide range in frequency spectrum based on the power spectral density is also used to confirm the chaotic behavior. In order to control the chaotic system and reach the desired level of a healthy person's glucose, a novel fuzzy high-order sliding mode control method has been proposed. Thus, in the control algorithm of the high-order sliding mode controller, all of the control gains computed by the fuzzy inference system accurately. Then the novel control algorithm is applied to the Bergman's mathematical model that is verified using the clinical data set. In this system, the control input is the amount of insulin injected into the body and the control output is the amount of blood glucose level at any moment. The simulation results of the closed-loop system in various conditions, along with the performance of the control system in disturbance presence, indicate the proper functioning of this controller at the settling time, overshoot and the control inputs.
topic chaos
glucose-insulin blood system
lyapunov exponent
sliding mode controller
fuzzy logic
url http://jacet.srbiau.ac.ir/article_13972_eff2c18ce90e4863fe9d27142d78f6ca.pdf
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