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arXiv · 2008.05245

Covid-19 and Flattening the Curve: a Feedback Control Perspective

Francesco Di Lauro·István Z. Kiss·Daniela Rus·Cosimo Della Santina
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Abstract

Many of the control policies that were put into place during the Covid-19 pandemic had a common goal: to flatten the curve of the number of infected people so that its peak remains under a critical threshold. This letter considers the challenge of engineering a strategy that enforces such a goal using control theory. We introduce a simple formulation of the optimal flattening problem, and provide a closed form solution.This is augmented through nonlinear closed loop tracking of the nominal solution, with the aim of ensuring close-to-optimal performance under uncertain conditions. A key contribution ofthis paper is to provide validation of the method with extensive and realistic simulations in a Covid-19 scenario, with particular focus on the case of Codogno - a small city in Northern Italy that has been among the most harshly hit by the pandemic.

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Francesco Di Lauro, István Z. Kiss, Daniela Rus, Cosimo Della Santina. 2020-08-12. Covid-19 and Flattening the Curve: a Feedback Control Perspective. https://doi.org/10.1109/lcsys.2020.3039322

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