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Higher Order Sliding Mode Control for Blood Glucose Regulation of Type 1 Diabetic Patients

Author

Listed:
  • Mounir Djouima

    (Electronics Department, LEA, University of Batna 2, Mostafa Benboulaid, Batna, Algeria)

  • Ahmad Taher Azar

    (Faculty of Computers and Information, Benha University, Benha, Egypt & School of Engineering and Applied Sciences, Nile University, Giza, Egypt)

  • Saïd Drid

    (LSP-IE, University of Batna 2, Batna, Mostafa Benboulaid, Algeria)

  • Driss Mehdi

    (University of Poitiers, Poitiers Cedex, France)

Abstract

Type 1 diabetes mellitus (T1DM) treatment depends on the delivery of exogenous insulin to obtain near normal glucose levels. This article proposes a method for blood glucose level regulation in type 1 diabetics. The control strategy is based on comparing the first order sliding mode control (FOSMC) with a higher order SMC based on the super twisting control algorithm. The higher order sliding mode is used to overcome chattering, which can induce some undesirable and harmful phenomena for human health. In order to test the controller in silico experiments, Bergman's minimal model is used for studying the dynamic behavior of the glucose and insulin inside human body. Simulation results are presented to validate the effectiveness and the good performance of this control technique. The obtained results clearly reveal improved performance of the proposed higher order SMC in regulating the blood glucose level within the normal glycemic range in terms of accuracy and robustness.

Suggested Citation

  • Mounir Djouima & Ahmad Taher Azar & Saïd Drid & Driss Mehdi, 2018. "Higher Order Sliding Mode Control for Blood Glucose Regulation of Type 1 Diabetic Patients," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 7(1), pages 65-84, January.
    • Handle: RePEc:igg:jsda00:v:7:y:2018:i:1:p:65-84
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    Citations

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    Cited by:

    1. Sayyar Ahmad & Charrise M. Ramkissoon & Aleix Beneyto & Ignacio Conget & Marga Giménez & Josep Vehi, 2021. "Generation of Virtual Patient Populations That Represent Real Type 1 Diabetes Cohorts," Mathematics, MDPI, vol. 9(11), pages 1-15, May.
    2. Turki Alsuwian & Muhammad Tayyeb & Arslan Ahmed Amin & Muhammad Bilal Qadir & Saleh Almasabi & Mohammed Jalalah, 2022. "Design of a Hybrid Fault-Tolerant Control System for Air–Fuel Ratio Control of Internal Combustion Engines Using Genetic Algorithm and Higher-Order Sliding Mode Control," Energies, MDPI, vol. 15(15), pages 1-23, August.

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