Robust Kalman filter design for discrete-time systems with Markovian jumping parameters

In this paper, the robust Kalman filtering problem for uncertain discrete-time linear systems with Markovian jumping parameters is addressed. It is assumed that the information about the jumping parameters is available, and the uncertainties are formulated by linear fractional transformation. We propose two methods for designing Markovian jumping filters so that the covariance of estimation error is bounded above. The main results are presented via a set of algebraic Riccati equations and a set of linear matrix inequalities.