Abstract
Interval analysis has been successfully applied to parameter and state estimation of noisy experimental data. However, obtaining efficient set estimators which are robust to outliers is still very difficult. This paper introduces new robust parameter and state estimation techniques in a bounded-error context in the presence of outliers. Several examples are provided concerning guaranteed parameter estimation of some chemical processes and the state tracking of aircrafts.
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