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Is it Curbing-spread of SARS-CoV-2 Variants by Considering Non-linear Predictive Control?
Mohadeseh Najafi1, Hamidreza Mortazavy Beni2, Ashkan Heydarian3
1Department of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar, Iran.
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.
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