Trajectory Tracking of Optimal Social Distancing Strategies with Application to a CoVid-19 Scenario

Lauro, Francesco Di; Kiss, Istvan; Rus, Daniela; Santina, Cosimo Della

This letter proposes the use of nonlinear feedback control to produce robust and reactive social distancing policies that can be adapted in response to an epidemic outbreak. % A trajectory tracking algorithm is proposed, and its effectiveness is analytically proven when acting on a low-dimensional approximation of the epidemics. % Means of mapping the inputs and output of this controller to the real network dynamics of the epidemics are introduced. % The strategy is tested with extensive simulations in a Covid-19 inspired 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. % The proposed algorithm generates dramatic reductions of epidemic levels, while maintaining a total level of social distancing close to the nominal optimum.