WITHDRAWN: Control of the COVID-19 System by Vaccination Using a New Control Engineering Technique
Abstract In this work, a novel control engineering method is proposed to achieve a control strategy by vaccination for the COVID-19 epidemic. A proper mathematical model with vaccination control is developed for the COVID-19 system based on the Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiological model after conducting some analyses and assumptions that reflect the COVID-19 features. Then, the proposed control law is designed using the feedback linearization approach and the H-infinity control framework. In addition, a model reference control is incorporated to ensure that satisfactory time responses are obtained. The Black Hole Optimization (BHO) technique is used to attain the optimality of the proposed control method. Following that, the reported statistics and vaccination plan of the Lombardy region of Italy are utilized to assess the effectiveness of the proposed control law. Ultimately, the simulation results illustrate that the proposed control law can effectively control the COVID-19 system and correctly perform the vaccination plan by tackling the system’s nonlinearity and uncertainty and realizing elegant asymptotic tracking characteristics with reasonable control effort..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
ResearchSquare.com - (2024) vom: 15. März Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ali, Hazem Ibrahim [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-1220281/v1 |
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| PPN (Katalog-ID): |
XRA034957979 |
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| 520 | |a Abstract In this work, a novel control engineering method is proposed to achieve a control strategy by vaccination for the COVID-19 epidemic. A proper mathematical model with vaccination control is developed for the COVID-19 system based on the Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiological model after conducting some analyses and assumptions that reflect the COVID-19 features. Then, the proposed control law is designed using the feedback linearization approach and the H-infinity control framework. In addition, a model reference control is incorporated to ensure that satisfactory time responses are obtained. The Black Hole Optimization (BHO) technique is used to attain the optimality of the proposed control method. Following that, the reported statistics and vaccination plan of the Lombardy region of Italy are utilized to assess the effectiveness of the proposed control law. Ultimately, the simulation results illustrate that the proposed control law can effectively control the COVID-19 system and correctly perform the vaccination plan by tackling the system’s nonlinearity and uncertainty and realizing elegant asymptotic tracking characteristics with reasonable control effort. | ||
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