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Robust SM Observer for COVID data prediction and Parameters Estimation

The prediction and observation of the growth, and the peaks reproduction of the Coronavirus are of main importance. In this study, we revisit the old deterministic SIR model and show its ability to describe the disease spread; Then we use it to try some observers to avoid acquisition perturbations and measurements imperfections. After finite time converging observations an output re-injection is used for parameters estimation. Note that the data are not provided by sensors which are regular in their measurements, synchronised in time and robust versus noise