Abstract
An early understanding of effective policy and transmission dynamics can help us prevent further outbreaks of the COVID-19. This article proposes a nonlinear adaptive control strategy based on effective policy to contain this epidemic. A mathematical model of nonlinear dynamics of the COVID-19 transmission in India is considered. The model also takes uncertainty into account. The control input calculated by the proposed controller prescribes the contact rate of the disease so that the number of infectious population converges to a desired zero value. The controller utilizes a Lyapunov theorem-based adaption law to be able to deal with modeling uncertainties, instability, and divergence. The controller performance on the nonlinear and uncertain model of the COVID-19 transmission has been investigated through a simulation study.
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