COVID-19 分阶延迟 SIQR 模型的优化控制分析

S. Suganya, V. Parthiban
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摘要

在本研究中,我们提出了带时间延迟的分数阶 COVID-19 模型的最优控制策略。研究了分数延迟模型解的存在性和唯一性。我们计算了基本重现数,并建立了模型在 Caputo 导数下的局部稳定性分析。我们以疫苗接种和治疗为时间控制参数,提出了一个分数阶延迟最优控制问题。我们推导出了最优控制的必要条件和充分条件。在 MATLAB 中,我们采用前向-后向扫频方法对所得到的分数延迟优化系统进行了数值求解。我们的研究结果表明,在模型中结合分数阶导数和时间延迟可以增强动态性,同时增加模型的复杂性。
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Optimal control analysis of fractional order delayed SIQR model for COVID-19

In this study, we propose an optimal control strategies for a fractional-order COVID-19 model with time delay. Existence and uniqueness of a solution to the fractional delay model are investigated. We compute the basic reproduction number and establish the local stability analysis of the model under the Caputo derivative. We develop a fractional order delayed optimal control problem based on vaccination and treatment as time-dependent control parameters. We derive the necessary and sufficient condition for optimal control. In MATLAB, the resulting fractional delay optimality system is numerically solved employing the forward–backward sweep method. Our findings suggest that combining fractional-order derivatives with time-delay in the model enhances dynamics while increasing model complexity.

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