H∞ filtering for a class of discrete-time Markovian jump systems with partially unknown transition probabilities and missing measurements

This paper is concerned with the H_∞ filtering problem for a class of discrete-time Markovian jump systems with partially unknown transition probabilities and missing measurements. The measurement missing is assumed to occur in a random way, and the missing probability for each measurement channel is governed by an individual random variable satisfying a certain probabilistic distribution over the interval [0 1]. Our attention is focused on the design of a filter such that, for the partially unknown transition probabilities and the admissible random measurements missing, the resulting filtering error system is stochastically stable. By using the mode-dependent Lypounov function, the linear matrix inequality (LMI) framework and sufficient conditions are derived to ensure stability of filtering error, and then the filter parameters are characterized by the solution to a set of LMIs, Illustractive direct current (dc) motor example is exploited to show the effectiveness of proposed design the procedures.