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Design modified second order sliding mode controller based on ST algorithm for blood glucose regulation systems

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Abstrakty
EN
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 dis-turbing 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 glu-cose deviation to a sudden rise in blood glucose.
Twórcy
  • Mustansiriyah University, College of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad, Iraq, ek_karam@yahoo.com
  • Mustansiriyah University, College of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad, Iraq, eman_hassony24@yahoo.com
Bibliografia
  • [1] 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.
  • [2] 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
  • [3] 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.
  • [4] 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).
  • [5] 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.
  • [6] 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.
  • [7] 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.
  • [8] 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.
  • [9] Hadi, E.A. (2019). Multi Objective Decision Maker for Single and Multi Robot Path Planning (MSc. thesis). University of Technology (Iraq).
  • [10] 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
  • [11] Levant, A. (1993). Sliding order and sliding accuracy in sliding mode control. Int J Control, 58(6), 1247–63.
  • [12] 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.
  • [13] 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.
  • [14] 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.
  • [15] Wang, D., Tan, D., & Liu, L. (2018). Particle swarm optimization algorithm: an overview. Soft Computing, 22(2), 387–408.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-bfcad3bf-920b-4d46-b6bc-671fb9df8979
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