Modelling and Nonlinear Optimal Control of the COVID-19 Pandemic in Connecticut
COVID-19 is an infectious disease which has resulted in an ongoing pandemic. This paper attempts to model the spread of the disease in the state of Connecticut, and formulate a nonlinear closed-loop feedback controller to minimize the number of infected. A model is first developed and studied. Difficulties in applying the controller - frequency of policy changes, lagging data, an unpredictable population - are explored.
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