Is it Curbing-spread of SARS-CoV-2 Variants by Considering Non-linear Predictive Control?

Although SARS-COV-2 started in 2019, its losses are still significant, and it takes victims. In the present study, the epidemic patterns of SARS-COV-2 disease have been investigated from the point of view of mathematical modeling. Also, the effect of quarantine has been considered. This mathematical model is designed in the form of fractional calculations along with a model predictive control (MPC) to monitor this model. The fractional-order model has the memory and hereditary properties of the system, which can provide more adjustable parameters to the designer. Because the MPC can predict future outputs, it can overcome the conditions and events that occur in the future. The results of the simulations show that the proposed nonlinear model predictive controller (NMPC) of fractional-order has a lower mean squared error in susceptible people compared to the optimal control of fractional-order (~3.6e-04 vs. 47.4). This proposed NMPC of fractional-order can be used for other models of epidemics.

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Publication Details

Journal
Biomedical Engineering and Computational Biology
Published
2025-04-16
DOI
https://doi.org/10.1177/11795972251321306
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
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article

Is it Curbing-spread of SARS-CoV-2 Variants by Considering Non-linear Predictive Control?

Ahmad Hajipour, Ashkan Heydarian, Samaneh Sadat Sajjadi, Hamidreza Mortazavy Beni et al.
Biomedical Engineering and Computational Biology
SARS-CoV-2 and COVID-19 Research
article

Is it Curbing-spread of SARS-CoV-2 Variants by Considering Non-linear Predictive Control?

Ahmad Hajipour, Ashkan Heydarian, Samaneh Sadat Sajjadi, Hamidreza Mortazavy Beni, Mohadeseh Najafi
article en

Abstract

Although SARS-COV-2 started in 2019, its losses are still significant, and it takes victims. In the present study, the epidemic patterns of SARS-COV-2 disease have been investigated from the point of view of mathematical modeling. Also, the effect of quarantine has been considered. This mathematical model is designed in the form of fractional calculations along with a model predictive control (MPC) to monitor this model. The fractional-order model has the memory and hereditary properties of the system, which can provide more adjustable parameters to the designer. Because the MPC can predict future outputs, it can overcome the conditions and events that occur in the future. The results of the simulations show that the proposed nonlinear model predictive controller (NMPC) of fractional-order has a lower mean squared error in susceptible people compared to the optimal control of fractional-order (~3.6e-04 vs. 47.4). This proposed NMPC of fractional-order can be used for other models of epidemics.

Biomedical Engineering and Computational BiologyVol. 16
Islamic Azad University, Science and Research Branch (IR), Hakim Sabzevari University (IR), Islamic Azad University of Arsanjan (IR)
Good health and well-being
Openalex Percentile: Top 89%
SARS-CoV-2 and COVID-19 Research
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