Non-fragile H∞ filtering for discrete stochastic Markov jump systems with intermittent measurements

This paper is devoted to the non-fragile H
_∞
filter design for discrete stochastic Markov jump systems against intermittent measurements. The measured outputs may be lost among the transmission from the plant to the filter. This phenomenon is modeled via a stochastic variable, which satisfies the Bernoulli random binary distribution. Without extra structure constraints on the introduced variable matrices, sufficient linear matrix inequalities conditions are established to guarantee the stochastic stability and the required H
_∞
performance of the filtering error system. Then, a numerical example shows the effectiveness of the proposed approach.