Event-triggered nonfragile H∞ filtering of Markov jump systems with imperfect transmissions

This paper is concerned with the event-triggered nonfragile H∞ filtering of Markov jump systems with interval variations. Integrating the sampler failure into the filter design, two independent random variables satisfying the Bernoulli distribution are utilized to describe the imperfect transmissions from sensor to event generator and event generator to filter, respectively. The resultant event-triggered scheme is represented by a stochastic form. With the help of stochastic analysis technique, sufficient conditions for the filtering error system to be stochastically stable with the required H∞ performance are formulated in terms of linear matrix inequalities. A structured vertex separation method is adopted to handle filter gains with interval variations. The validity of the proposed approach is verified by an RLC circuit.