Design and Tuning of Control system for blood Glucose level with artificial pancreas using harmony search Algorithm

Authors

  • S S Pathamanabha Swaroopan Rajah Muthiah Medical College, Annamalai University, Chidambaram, India Author
  • Chinmaya Ranjan Pattanaik Department of Computer Science and Engineering ,Ajay Binay Institute of Technology, Cuttack, Odisha, India Author
  • Shiva Shankar Reddy Department Of Computer Science and Engineering, SRKR Engineering College, Chinna Amiram, Bhimavaram, Andhra Pradesh, India Author
  • E. Ahila Devi Department of Instrumentation and Control Engineering, St.Joseph's college of Engineering. Chennai, India Author
  • Sujatha krishamoorthy Department of computer science, Wenzhou kean University, Zhejiang province , Wenzhou, China Author

DOI:

https://doi.org/10.61841/gfxtpv32

Keywords:

psychosocial, diabetes, stress, IMC control, PID, Harmony Search Algorithm, Blood Glucose

Abstract

Diabetes adds psychosocial issues to every day of life. Stress can be a major obstacle to effective glucose control. The artificial pancreas developed to control the glucose level effectively than manual injection. The closed loop controller algorithm designing procedure is proposed in this paper by considering the Bergman Minimal Model as a diabetes dynamic. Two Control strategies are designed such as proportional & Derivative controller (PD) and Internal Model Controller (IMC), and then the controller gains are optimally tuned using harmony search algorithm. The performance of controller algorithm is compared and analyzed by the closed loop simulation results.

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References

1. The Psychological Impact of Diabetes (2019). Diabetes Research & Wellness Foundation. Available at: https://www.drwf.org.uk/news-and-events/news/psychological-impact-diabetes (Accessed: June 04, 2019).

2. Abu-Rmileh, A. & Garcia-Gabin. “Hypoglycemia Prevention in Closed-Loop Artificial Pancreas for Patients with Type 1 Diabetes.” INTECH Open Access Publisher, 2010.

3. Boiroux, D. Model Predictive Control Algorithms for Pen and Pump Insulin Administration. Ph.D. Thesis, DTU Compute, 2012.

4. Gharghory, S. M. & Mahmoud, M. “Low Power Fuzzy Control System for Adjusting the Blood Glucose Level.” Microelectronics (ICM), 28th International Conference, IEEE Xplore, 2017.

5. Chee, F., Fernando, T. L., & Savkin, A. V. “Expert PID Control System for Blood Glucose Control in Critically Ill Patients.” IEEE Transactions.

6. Pagkalos, I., Herrero, P., Toumazou, C., & Georgiou, P. “Bio-Inspired Glucose Control in Diabetes Based on an Analogue Implementation of a β-Cell Model.” IEEE Transactions on Biomedical Circuits and Systems, 8(2), 2014, pp. 186–195.

7. Sivaramakrishnan, N., Lakshmanaprabu, S. K., & Muvvala, M. V. “Optimal Model-Based Control for Blood Glucose Insulin System Using Continuous Glucose Monitoring.” Journal of Pharmaceutical Sciences and Research, 9(4), 2017, p. 465.

8. Bergman, R. N. “Minimal Model: Perspective from 2005.” Hormone Research in Paediatrics, 64(Suppl. 3), 2005, pp. 8–15.

9. Bequette, B. W. Process Control: Modeling, Design, and Simulation. Prentice Hall Professional, 2003.

10. Merzougui, A., Hasseine, A., & Laiadi, D. “Application of the Harmony Search Algorithm to Calculate Interaction Parameters in Liquid–Liquid Phase Equilibrium Modeling.” Fluid Phase Equilibria, 324, 2012, pp. 94–101.

11. Geem, Z. W. (Ed.). Music-Inspired Harmony Search Algorithm: Theory and Applications. Studies in Computational Intelligence, Springer, 2009.

12. Malik, Salman Farcy Jamal Mohamed. “Particle Swarm Optimisation Based Blood Glucose Control in Type 1 Diabetes.” Master Thesis, Kaunas University of Technology, 2018.

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Published

30.05.2020

Issue

Vol. 24 No. 10 (2020): 24 (10) 2020

Section

Articles

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How to Cite

Swaroopan, S. S. P., Pattanaik, C. R., Reddy, S. S., Devi, E. A., & krishamoorthy, S. (2020). Design and Tuning of Control system for blood Glucose level with artificial pancreas using harmony search Algorithm . International Journal of Psychosocial Rehabilitation, 24(10), 1610-1620. https://doi.org/10.61841/gfxtpv32