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首页> 外文会议>Multidisciplinary International Symposium on Positive Systems: Theory and Applications >Interval Observers for SIR Epidemic Models Subject to Uncertain Seasonality
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Interval Observers for SIR Epidemic Models Subject to Uncertain Seasonality

机译：对于季节性不确定的SIR流行模型的间隔观察者

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摘要

Epidemic models describe the establishment and spread of infectious diseases. Among them, the SIR model is one of the simplest, involving exchanges between three compartments in the population, that represent respectively the number of susceptible, infective and recovered individuals. The issue of state estimation is considered here for such a model, subject to seasonal variations and uncertainties in the transmission rate. Assuming continuous measurement of the number of new infectives per unit time, a class of interval observers with estimate-dependent gain is constructed and analyzed, providing lower and upper bounds for each state variable at each moment in time. The dynamical systems that describe the evolution of the errors are monotonous. Asymptotic stability is ensured by appropriate choice of the gain components as a function of the state estimate, through the use of a common linear Lyapunov function. Numerical experiments are presented to illustrate the method.
机译：流行病模型描述了传染病的建立和传播。其中，SIR模型是最简单的，涉及群体中的三个隔间之间的交换之一，分别表示易感，感染性和恢复的个体的数量。此处考虑出现状态估计的问题，但这种模型在传输速率下进行季节性变化和不确定性。假设每单位时间的新感染性的数量连续测量，构造和分析了一类具有估计依赖性增益的间隔观察者，为每个时刻的每个状态变量提供下限和上限。描述误差演变的动态系统是单调的。 Asymptotic stability is ensured by appropriate choice of the gain components as a function of the state estimate, through the use of a common linear Lyapunov function.提出了数值实验以说明该方法。

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