Covid-19 and Flattening the Curve: A Feedback Control Perspective
Name
2008.05245.pdf
Description
Accepted version
Size
2.57 MB
Format
Adobe PDF
Checksum (MD5)
a2519be45b4297d3733cfc76815d8498
Author(s)
Di Lauro, Francesco
Kiss, Istvan Zoltan
Rus, Daniela L
Della Santina, Cosimo
Date Issued
November 2020
Journal
IEEE Control Systems Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Di Lauro, Francesco et al. "Covid-19 and Flattening the Curve: A Feedback Control Perspective." IEEE Control Systems Letters 5, 4 (October 2021): 1435 - 1440 © 2021 IEEE
Version
Original manuscript
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/lcsys.2020.3039322
