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

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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:   (1124 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]   (323 Downloads)    
Type of Article: Research paper | Subject: COVID-19
Received: 2021/01/28 | Accepted: 2021/02/12 | Published: 2021/02/28

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