通过基本配方对COVID-19的社交距离进行反控制
Michel Fliess1,2, Cédric Join3,2, Alberto d'Onofrio4
1École polytechnique, LIX (CNRS, UMR 7161), 91128 Palaiseau, France.
概括
本研究使用SIR模型来创建用于COVID-19控制的社交距离策略. 我们的发现为开放循环场景和强大的反控制提供了简单的公式,减少了对精确恢复率数据的需求.
科学领域:
- 流行病学 流行病学
- 控制理论 控制理论
- 数学建模的数学建模
背景情况:
- 针对COVID-19的减缓工作在很大程度上依赖于社交距离.
- 经典的SIR (易感-传染-恢复) 流行病模型是了解疾病传播的基本工具.
研究的目的:
- 为COVID-19等传染病制定有效的社会距离控制策略.
- 为了利用SIR模型的特性,在实际公共卫生决策中发挥作用.
主要方法:
- 使用SIR模型,将感染率作为控制变量.
- 应用差分平面度来推导开放循环场景的封闭形式控制公式.
- 实现无模型的控制反循环,以提高稳定性.
主要成果:
- 为开放式循环社会距离的基本封闭式公式得出.
- 控制策略在不确定性和模型不匹配方面表现出了显著的稳定性.
- 对于拟议的控制策略来说,对恢复率的准确知识并不必不可少.
结论:
- 这些公式可以帮助决策者实施有效的社交距离措施.
- 无模型控制为管理流行病传播提供了一种强有力的方法.
- 这项研究为优化流行病期间的公共卫生干预提供了有价值的框架.
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