DESIGN OF MODIFIED SECOND ORDER SLIDING MODE CONTROLLER BASED ON ST ALGORITHM FOR BLOOD GLUCOSE REGULATION SYSTEMS
Article Sidebar
Open full text
Issue Vol. 16 No. 2 (2020)
-
ANALYTICS AND DATA SCIENCE APPLIED TO THE TRAJECTORY OUTLIER DETECTION
Alexis J. LOPEZ, Perfecto M. QUINTERO, Ana K. HERNANDEZ5-17
-
DESIGN OF MODIFIED SECOND ORDER SLIDING MODE CONTROLLER BASED ON ST ALGORITHM FOR BLOOD GLUCOSE REGULATION SYSTEMS
Ekhlas H. KARAM, Eman H. JADOO18-31
-
MEASURING PROPENSITY OF ONLINE PURCHASE BY USING THE TAM MODEL: EVIDENCE FROM ITALIAN UNIVERSITY STUDENTS
Maria CORDENTE-RODRIGUEZ, Simone SPLENDIANI, Patrizia SILVESTRELLI32-52
-
CONTROLLING THE MEAN ARTERIAL PRESSURE BY MODIFIED MODEL REFERENCE ADAPTIVE CONTROLLER BASED ON TWO OPTIMIZATION ALGORITHMS
Rawaa HAAMED, Ekhlas HAMEED53-67
-
A CUSTOMER-CENTRIC APPLICATION FOR A CINEMA HOUSE
Raphael Olufemi AKINYEDE, Temitayo Elijah BALOGUN, Abiodun Boluwade ROTIMI, Oluwasefunmi Busola FAMODIMU68-79
-
FUZZY CONTROLLER OF MODEL REDUCTION DISTILLATION COLUMN WITH MINIMAL RULES
Nasir ALAWAD, Afaf ALSEADY80-94
-
EVALUATION OF ROBOTIC CLEANING TECHNOLOGIES: PRESERVING A BRITISH ICONIC BUILDING
Ahmed A.H. HAQQANI, Seenu N, Mukund JANARDHANAN, Kuppan Chetty RM95-111
-
PERFORMANCE ANALYSIS AND EVALUATION OF MASSIVE MIMO SYSTEM
Muaayed F. AL-RAWI, Izz K. ABBOUD, Nasir A. AL-AWAD112-119
Archives
-
Vol. 18 No. 4
2022-12-30 8
-
Vol. 18 No. 3
2022-09-30 8
-
Vol. 18 No. 2
2022-06-30 8
-
Vol. 18 No. 1
2022-03-30 7
-
Vol. 17 No. 4
2021-12-30 8
-
Vol. 17 No. 3
2021-09-30 8
-
Vol. 17 No. 2
2021-06-30 8
-
Vol. 17 No. 1
2021-03-30 8
-
Vol. 16 No. 4
2020-12-30 8
-
Vol. 16 No. 3
2020-09-30 8
-
Vol. 16 No. 2
2020-06-30 8
-
Vol. 16 No. 1
2020-03-30 8
-
Vol. 15 No. 4
2019-12-30 8
-
Vol. 15 No. 3
2019-09-30 8
-
Vol. 15 No. 2
2019-06-30 8
-
Vol. 15 No. 1
2019-03-30 8
-
Vol. 14 No. 4
2018-12-30 8
-
Vol. 14 No. 3
2018-09-30 8
-
Vol. 14 No. 2
2018-06-30 8
-
Vol. 14 No. 1
2018-03-30 7
Main Article Content
DOI
Authors
Abstract
The type1 of diabetes is a chronic situation characterized by abnormally high glucose levels in the blood. Persons with diabetes characterized by no insulin secretion in the pancreas (ß-cell) which also known as insulin-dependent diabetic Mellitus (IDDM). In order to keep the levels of glucose in blood near the normal ranges (70-110mg/dl), the diabetic patients needed to inject by external insulin from time to time. In this paper, a Modified Second Order Sliding Mode Controller (MSOSMC) has been developed to control the concentration of blood glucose levels under a disturbing meal. The parameters of the suggested design controller are optimized by using chaotic particle swarm optimization(CPSO) technique, the model which is used to represent the artificial pancreas is a minimal model for Bergman. The simulation was performed on a MATLAB/ SIMULINK to verify the performance of the suggested controller. The results showed the effectiveness of the proposed MSOSMC in controlling the behavior of glucose deviation to a sudden rise in blood glucose.
Keywords:
References
Abu-Rmileh, A., & Garcia-Gabin, W. (2011). Smith predictor sliding mode closed-loop glucose controller in type 1 diabetes. IFAC Proc. Vol., 18(PART 1), 1733–1738. DOI: https://doi.org/10.3182/20110828-6-IT-1002.01213
Alam, W., Ali, N., Ahmad, S., & Iqbal, J. (2018). Super twisting control algorithm for blood glucose regulation in type 1 diabetes patients. In 2018 15th International Bhurban Conference on Applied Sciences and Technology (IBCAST) (pp. 298–303). IEEE. http://doi.org/10.1109/IBCAST.2018.8312239 DOI: https://doi.org/10.1109/IBCAST.2018.8312239
Amet, L., Ghanes, M., & Barbot, J-P. (2012). HOSM control under quantization and saturation constraints: Zig-Zag design solutions. In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC) (pp. 5494–5498). Maui, HI. http://doi.org/10.1109/CDC.2012.6426197. DOI: https://doi.org/10.1109/CDC.2012.6426197
Basher, A.S. (2017). Design fuzzy control system for blood glucose level for type-1 diabetes melitus patients using ga a simulation study (Msc. Thesis). The Islamic University (Gaza).
Bergman, R.N., Phillips, L.S., & Cobelli, C. (1981). Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose. The Journal of clinical investigation. 68(6), 1456–1467. DOI: https://doi.org/10.1172/JCI110398
Djouima, M., Azar, A.T., Drid, S., & Mehdi, D. (2018). Higher Order Sliding Mode Control for Blood Glucose Regulation of Type 1 Diabetic Patients. International Journal of System Dynamics Applications (IJSDA), 7(1), 65–84. DOI: https://doi.org/10.4018/IJSDA.2018010104
Fisher, M.E. (1991). A semiclosed-loop algorithm for the control of blood glucose levels in diabetics. IEEE Trans Biomed Eng, 38(1), 57–61. DOI: https://doi.org/10.1109/10.68209
Garcia-Gabin, W., Zambrano, D., Bondia, J., & Vehí, J. (2009). A sliding mode predictive control approach to closed-loop glucose control for type1 diabetes. IFAC Proceedings Volumes, 42(12), 85–90. DOI: https://doi.org/10.3182/20090812-3-DK-2006.0046
Hadi, E.A. (2019). Multi Objective Decision Maker for Single and Multi Robot Path Planning (MSc. thesis). University of Technology (Iraq).
Kaveh, P., & Shtessel, Y.B. (2006). Blood Glucose Regulation in Diabetics Using Sliding Mode Control Techniques. In 2006 Proceeding of the Thirty-Eighth Southeastern Symposium on System Theory (pp. 171–175). Cookeville, TN. http://doi.org/10.1109/SSST.2006.1619068 DOI: https://doi.org/10.1109/SSST.2006.1619068
Levant, A. (1993). Sliding order and sliding accuracy in sliding mode control. Int J Control, 58(6), 1247–63. DOI: https://doi.org/10.1080/00207179308923053
Matraji, I., Al-Durra, A., & Errouissi, R. (2018). Design and experimental validation of enhanced adaptive second-order SMC for PMSG-based wind energy conversion system. International Journal of Electrical Power & Energy Systems, 103, 21–30. DOI: https://doi.org/10.1016/j.ijepes.2018.05.022
Parsa, N.T., Vali, A., & Ghasemi, R. (2014). Back Stepping Sliding Mode Control of Blood Glucose for Type I Diabetes. World Academy of Science, Engineering and Technology, International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering, 8(11), 779–783.
Sylvester, D.D., & Munje, R.K. (2017). Back stepping SMC for blood glucose control of type-1 diabetes mellitus patients. International Journal of Engineering Technology Science and Research, 4(5), 1–7.
Wang, D., Tan, D., & Liu, L. (2018). Particle swarm optimization algorithm: an overview. Soft Computing, 22(2), 387–408. DOI: https://doi.org/10.1007/s00500-016-2474-6
Article Details
Abstract views: 339
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
