State estimation with uncertain parametric models

Abstract: Develops a robust estimation procedure for state-space models with parametric uncertainties. Compared with existing robust filters, the proposed filter performs data regularization rather than de-regularization. It is shown that, under certain stabilizability and detectability conditions, the steady-state filter is stable and that, for quadratically-stable models, it guarantees a bounded error variance.