Robust filters for Markovian jump linear systems under sampled measurements

In this paper, a new class of Markovian jump linear system model with polytopic parameter uncertainty, continuous disturbance and discrete disturbance is introduced. The transition rate matrix of the Markov process and the parameters of the system are either exactly known, or unknown but belong to a given polytope. The general criteria for the stochastic stability of this model and the method for designing a robust stable linear time-invariant H ∞ filter under sampled measurements are derived in terms of certain linear matrix inequalities (LMIs). Finally, a numerical example is given to show that the method is effective and feasible.