Robust Kalman filtering for discrete state-delay systems

A robust estimator design methodology has been developed for a class of linear uncertain discrete-time systems. It extends the Kalman filter to the case in which the underlying system is subject to norm-bounded uncertainties and constant state delay. A linear state estimator is constructed via a systematic procedure such that the estimation error covariance is guaranteed to lie within a certain bound for all admissible uncertainties. The solution is given in terms of two Riccati equations involving scaling parameters. A numerical example is provided to illustrate the theory.