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
![]() |
PDF
- Accepted Version
Download (2MB) |
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: | 25 Jun 2021 09:00 |
URI: | http://sro.sussex.ac.uk/id/eprint/97123 |
View download statistics for this item
📧 Request an update