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

In this paper, the robust Kalman filtering problem for uncertain continuous-time linear systems with Markovian jumping parameters is addressed. The uncertainties are formulated by linear fractional transformation. After the system stochastic stability is defined, a state estimator design method is developed so that the covariance of estimation error is bounded above. A solution method involving, a set of coupled Riccati equations is proposed, and then converted into an optimization procedure based on linear matrix inequality.