Robust state estimation and model validation for discrete-time uncertain systems with a deterministic description of noise and uncertainty

The paper presents a new approach to robust state estimation for a class of uncertain discrete-time systems with a deterministic description of noise and uncertainty. The main result is a recursive scheme for constructing an ellipsoidal state estimation set of all states consistent with the measured output and the given noise and uncertainty description. The paper also includes a result on model validation whereby it can be determined if the assumed model is consistent with measured data.