Covid-19 and flattening the curve: a feedback control perspective

Di Lauro, Francesco, Kiss, István Zoltán, Rus, Daniela and Della Santina, Cosimo (2021) Covid-19 and flattening the curve: a feedback control perspective. IEEE Control Systems Letters, 5 (4). pp. 1435-1440. ISSN 2475-1456

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Abstract

Many of the 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 of this letter 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.

Item Type: Article
Schools and Departments: School of Mathematical and Physical Sciences > Mathematics
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 15 Feb 2021 08:46
Last Modified: 21 Jun 2021 14:44
URI: http://sro.sussex.ac.uk/id/eprint/97123

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