| Autor: |
Mu'tamar, Khozin, Naiborhu, Janson, Saragih, Roberd |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2480 Issue 1, p1-10, 10p |
| Abstrakt: |
The COVID-19 virus is still a worldwide problem even though it has been two years since it was first discovered. Vaccination is an alternative solution to reduce the spread of COVID-19. Generally, vaccination designs in epidemic models use the Pontryagin minimum principle. In this article, we present the design control of vaccination in an epidemic model for cases of the spread of the COVID-19 virus. The model used is the Susceptible, Infected, and Removed (SIR) model using data from daily cases in the Riau region for the period September - October 2020. The model parameters are estimated using Particle Swarm Optimization. The control design was done using the backstepping method combined with input-output feedback linearization (IOFL). The simulation results show that by using appropriate backstepping control parameters, the backstepping control provides better control performance than the PMP method. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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