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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| Format: | Article |
| Language: | English |
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Science and Research Branch,Islamic Azad University
2019-05-01
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| Series: | Journal of Advances in Computer Engineering and Technology |
| Subjects: | |
| Online Access: | http://jacet.srbiau.ac.ir/article_13972_eff2c18ce90e4863fe9d27142d78f6ca.pdf |
| _version_ | 1818876159237029888 |
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| author | Saeid Khajehvand Seyed Mahdi Abtahi |
| author_facet | Saeid Khajehvand Seyed Mahdi Abtahi |
| author_sort | Saeid Khajehvand |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-19T13:37:57Z |
| format | Article |
| id | doaj.art-19035922345a40aeb195bce332c93462 |
| institution | Directory Open Access Journal |
| issn | 2423-4192 2423-4206 |
| language | English |
| last_indexed | 2024-12-19T13:37:57Z |
| publishDate | 2019-05-01 |
| publisher | Science and Research Branch,Islamic Azad University |
| record_format | Article |
| series | Journal of Advances in Computer Engineering and Technology |
| spelling | doaj.art-19035922345a40aeb195bce332c934622022-12-21T20:19:07ZengScience 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 |
| 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 |
| title | 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_short | 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 |
| 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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