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MPC Controllers in SIIR Epidemic Models. / Косьянов, Никита Олегович; Губар, Елена Алексеевна; Тайницкий, Владислав Александрович.

In: Computation, Vol. 11, No. 9, 173, 04.09.2023.

Research output: Contribution to journal › Article › peer-review

Harvard

Косьянов, НО, Губар, ЕА & Тайницкий, ВА 2023, 'MPC Controllers in SIIR Epidemic Models', Computation, vol. 11, no. 9, 173. https://doi.org/10.3390/computation11090173

APA

Косьянов, Н. О., Губар, Е. А., & Тайницкий, В. А. (2023). MPC Controllers in SIIR Epidemic Models. Computation, 11(9), [173]. https://doi.org/10.3390/computation11090173

Vancouver

Косьянов НО, Губар ЕА, Тайницкий ВА. MPC Controllers in SIIR Epidemic Models. Computation. 2023 Sep 4;11(9). 173. https://doi.org/10.3390/computation11090173

Author

Косьянов, Никита Олегович ; Губар, Елена Алексеевна ; Тайницкий, Владислав Александрович. / MPC Controllers in SIIR Epidemic Models. In: Computation. 2023 ; Vol. 11, No. 9.

BibTeX

@article{6f7bbf842174448bba61ee41c9ab2fe6,
title = "MPC Controllers in SIIR Epidemic Models",
abstract = "Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of many countries. Hence, it is therefore important to minimize the economic damage, which includes both loss of work and treatment costs, quarantine costs, etc. Recent studies have presented many different models describing the dynamics of virus spread, which help to analyze the epidemic outbreaks. In the current work we focus on finding solutions that are robust to noise and take into account the dynamics of future changes in the process. We extend previous results by using a nonlinear model-predictive-control (MPC) controller to find effective controls. MPC is a computational mathematical method used in dynamically controlled systems with observations to find effective controls.",
author = "Косьянов, {Никита Олегович} and Губар, {Елена Алексеевна} and Тайницкий, {Владислав Александрович}",
year = "2023",
month = sep,
day = "4",
doi = "10.3390/computation11090173",
language = "English",
volume = "11",
journal = "Computation",
issn = "2079-3197",
publisher = "MDPI AG",
number = "9",

}

RIS

TY - JOUR

T1 - MPC Controllers in SIIR Epidemic Models

AU - Косьянов, Никита Олегович

AU - Губар, Елена Алексеевна

AU - Тайницкий, Владислав Александрович

PY - 2023/9/4

Y1 - 2023/9/4

N2 - Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of many countries. Hence, it is therefore important to minimize the economic damage, which includes both loss of work and treatment costs, quarantine costs, etc. Recent studies have presented many different models describing the dynamics of virus spread, which help to analyze the epidemic outbreaks. In the current work we focus on finding solutions that are robust to noise and take into account the dynamics of future changes in the process. We extend previous results by using a nonlinear model-predictive-control (MPC) controller to find effective controls. MPC is a computational mathematical method used in dynamically controlled systems with observations to find effective controls.

AB - Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of many countries. Hence, it is therefore important to minimize the economic damage, which includes both loss of work and treatment costs, quarantine costs, etc. Recent studies have presented many different models describing the dynamics of virus spread, which help to analyze the epidemic outbreaks. In the current work we focus on finding solutions that are robust to noise and take into account the dynamics of future changes in the process. We extend previous results by using a nonlinear model-predictive-control (MPC) controller to find effective controls. MPC is a computational mathematical method used in dynamically controlled systems with observations to find effective controls.

UR - https://www.mendeley.com/catalogue/c8ff7cd6-5419-3df3-b2d9-107236ebb971/

U2 - 10.3390/computation11090173

DO - 10.3390/computation11090173

M3 - Article

VL - 11

JO - Computation

JF - Computation

SN - 2079-3197

IS - 9

M1 - 173

ER -

ID: 111515466