Reference Tracking Control of a Nonlinear Epidemiological Model with State Estimation

In this paper, a reference tracking controller for an 8-compartment epidemic model is proposed. The dynamical model describing the disease spread and progression is given in nonlinear input-affine form. The manipulable input is the transmission rate, while the output to be tracked is the number of i...

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Bibliographic Details
Main Authors: Csutak, Balazs, Szederkenyi, Gabor
Format: Conference Proceeding
Language:English
Subjects:
compartmental models
Computational modeling
COVID-19
epidemiological models
Extended Kalman Filter
Feedback linearization
nonlinear control
Robustness
SEIR model
Sociology
Trajectory
Uncertain systems
Uncertainty
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Summary:In this paper, a reference tracking controller for an 8-compartment epidemic model is proposed. The dynamical model describing the disease spread and progression is given in nonlinear input-affine form. The manipulable input is the transmission rate, while the output to be tracked is the number of infected people. The model parameters correspond to the COVID-19 pandemic. The control design uses a simple SEIR model and it is based on feedback linearization combined with extended Kalman filter for state estimation. Simulation results show good tracking performance even with model mismatch and significant parameter uncertainty.
ISSN:2576-3555
DOI:10.1109/CoDIT58514.2023.10284317