Volume 14, Issue 5 (Journal of Control, Vol. 14, No. 5, Special Issue on COVID-19 2021)                   JoC 2021, 14(5): 79-88 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Rezaei Bahrmand M, Khaloozadeh H, Reihani Ardabili P. Design and implementation of a model predictive controller for the COVID-19 spread restraint in Iran. JoC. 2021; 14 (5) :79-88
URL: http://joc.kntu.ac.ir/article-1-837-en.html
1- Payamenoor university
2- K. N. Toosi University of Technology
Abstract:   (1358 Views)
In this paper, a model is proposed based on the different levels of social restrictions for the COVID-19 spread restraint in Iran. Also, a Genetic Algorithm (GA) identifies parameters of model using reported main data from the Iranian Ministry of Health and simulated data based on proposed model. Whereas Model Predictive Control (MPC) is a popular method which has been widely used in process control, after the discretization of model by a common method like Euler method, then we can consider the appropriate constraints and solve online optimization problem. In this paper, we have shown that the MPC controller able to flatten infected (symptomatic) individual curve and decrease its peak by applying the different levels of social restrictions. Numerical example and simulation results, based on main data, are given to illustrate the capability of this method.
Full-Text [PDF 811 kb]   (379 Downloads)    
Type of Article: Research paper | Subject: COVID-19
Received: 2021/01/28 | Accepted: 2021/02/12 | Published: 2021/02/28

References
1. T. van den Boom and A. Stoorvogel. "Model Predictive Control", CRC Press, 2010.
2. World HealthOrganization. https://www.who.int/emergencies/diseases/novel-coronavirus.
3. S. Zhao, H. Chen, "Modeling the epidemic dynamics and control of COVID-19 outbreak in China", Quantitative Biology 8 (2020) 11-19. [DOI:10.1007/s40484-020-0199-0]
4. Bedford, J., Farrar, J., Ihekweazu, C., Kang, G., Koopmans, M., Nkengasong, J. (2019)."A new twenty-frst century science for effective epidemic response."Nature, 575(7781), 130-136. [DOI:10.1038/s41586-019-1717-y]
5. Chudik, A., Pesaran, M. H., &Rebucci, A. (2020). "Voluntary and mandatory socialdistancing: Evidence on COVID-19 exposure rates from chinese provinces andselected countries. "Technical Report.National Bureau of Economic Research. [DOI:10.3386/w27039]
6. Del Rio, C., &Malani, P. N. (2020). "Covid-19 new insights on a rapidly changing epidemic." JAMA. [DOI:10.1001/jama.2020.3072]
7. J. Wu, B. Tang, N.L. Bragazzi, K. Nah, Z.(2020) "Mc Carthy Quantifying the role of social distancing, personal protection and case detection in mitigating covid-19outbreak in Ontario, Canada." J Math Ind, 10 (1) (2020), pp. 1-12. [DOI:10.1186/s13362-020-00083-3]
8. Hellewell, J., Abbott, S., Gimma, A., Bosse, N. I., Jarvis, C. I., Russell, T. W., Sun, F.,et al. (2020). "Feasibility of controlling COVID-19 outbreaks by isolation of cases andcontacts. "The Lancet Global Health. [DOI:10.1016/S2214-109X(20)30074-7]
9. Eichenbaum, M. S., Rebelo, S., &Trabandt, M. (2020)." The macroeconomics of epidemics." Working Paper.National Bureau of Economic Research. https://doi.org/10.3386/w26882 [DOI:10.3386/w26882.]
10. Gormsen, N. J., & Koijen, R. S. J. (2020). " Coronavirus: Impact on stock prices and growt expectations" (pp. 1-27). Working Paper of the University of Chicago. [DOI:10.3386/w27387]
11. Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020). "Projecting the transmission dynamics of SARS-COV-2 through the post pandemic period." Science. https://doi.org/10.1101/2020.03.04.20031112 [DOI:10.1126/science.abb5.]
12. Piunovskiy, A., Plakhov, A., & Tumanov, M. (2020). "Optimal impulse control of a sirepidemic. "Optimal Control Applications and Methods, 41(2), 448-468. https://doi.org/10.1002/oca.2552 [DOI:10.1002/oca.2552.]
13. Ullah, S., Khan, M. (2020). " Modeling the impact of nonpharmaceutical interventions on the dynamics of novelCoronavirus with optimal control analysis with a case study." Chaos Solitons and Fractals. [DOI:10.1016/j.chaos.2020.110075]
14. Perkins,T.A., Guido España, G.. (2020)."Optimal Control of the COVID-19 Pandemic with Non-pharmaceutical Interventions".Bulletin of Mathematical Biology, 82-118. [DOI:10.1007/s11538-020-00795-y]
15. Obsu, L.L., Balcha, S. (2020)."Optimal control strategies for the transmission risk of COVID-19. JOURNAL OF BIOLOGICAL DYNAMICS". VOL. 14, NO. 1, 590-607. https://doi.org/10.1080/17513758.2020.1788182 [DOI:10.1080/17513758.2020.1788182.]
16. Péni,T., Csutak,B., Szederkényi,G., Röst,G.. (2020). "Nonlinear model predictive control with logic constraints for COVID-19 management". NonlinearDyn (2020) 102:1965-1986. [DOI:10.1007/s11071-020-05980-1]
17. Kohler, € J., Schwenkel, L., Koch, A., Berberich, J., Pauli, P., & Allgower, F. (2020)."Robustand optimal predictive control of the COVID-19 outbreak ".arXiv:2005.03580. [DOI:10.1016/j.arcontrol.2020.11.002]
18. Zurakowski, R., Messina, M. J., Tuna, S. E., & Teel, A. R. (2004). "HIV treatment scheduling via robust nonlinear model predictive control," Vol. 1. 2004 5th Asian control conference (IEEE cat. no. 04ex904) (pp. 25-32). IEEE.
19. Hosseini,E., Ghafoor, K.Z, Emrouznejad. (2020)." A. COVID-19 Optimizer Algorithm, Modeling and Controlling of Coronavirus Distribution Process ".IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 24, NO. 10, OCTOBER 2020 [DOI:10.1109/JBHI.2020.3012487]
20. Kucharski, A. J., Russell, T. W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., Munday, J. D., et al. (2020). "Early dynamics of transmission and control of COVID-19: A mathematical modelling study. The Lancet Infectious Diseases." [DOI:10.1016/S1473-3099(20)30144-4]
21. Kermack, W. O., & Mc Kendrick, A. G. (1927). "A contribution to the mathematical theory of epidemics." Proceedings of the Royal Society A, 115, 700-721. [DOI:10.1098/rspa.1927.0118]
22. Keeling, M. J., & Rohani, P. (2011). "Modeling infectious diseases in humans and animals." [DOI:10.2307/j.ctvcm4gk0]
23. Robinson, M., & Stilianakis, N. I. (2013). "A model for the emergence of drug resistance in the presence of asymptomatic infections." Mathematical Biosciences, 243, 163-177. [DOI:10.1016/j.mbs.2013.03.003]
24. Arino, J., Brauer, F., van-den Driessche, P., Watmough, J., & Wu, J. (2008). " How will country-based mitigation measures influence the course of the COVID-19 epidemic? " Journal of Theoretical Biology, 253, 118-130. [DOI:10.1016/j.jtbi.2008.02.026]
25. Camacho, E. F., &Bordons, C. (2013). "Model predictive control. Springer Science Business Media."
26. Wu, J., Tang, B., Bragazzi, N., Nah, K., McCarthy, Z. (2020)."Quantifying the role of social distancing, personal protection andcase detection in mitigating COVID-19 outbreak in Ontario ", Canada. J. Math. Ind. 10(1), 15 (2020). [DOI:10.1186/s13362-020-00083-3]
27. Bastos, S. B., & Cajueiro, D. O. (2020). " Modeling and forecasting the early evolution of the covid-19 pandemic in Brazil ". arXiv:2003.14288. [DOI:10.1038/s41598-020-76257-1]
28. راهنمای جامع استانداردهای اعتبار بخشی ملی بیمارستان¬های ایران. وزارت بهداشت، درمان و آموزش پزشکی کشور. ویرایش چهارم، سال 1398.

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2021 CC BY-NC 4.0 | Journal of Control

Designed & Developed by : Yektaweb