Abstract
In this paper, the distributed ${H_{\infty }}$ state estimation problem is investigated for a class of filtering networks with time-varying switching topologies and packet losses. In the filter design, the time-varying switching topologies, partial information exchange between filters, the packet losses in transmission from the neighbor filters and the channel noises are simultaneously considered. The considered topology evolves not only over time, but also by event switches which are assumed to be subjects to a nonhomogeneous Markov chain, and its probability transition matrix is time-varying. Some novel sufficient conditions are obtained for ensuring the exponential stability in mean square and the switching topology-dependent filters are derived such that an optimal ${H_{\infty }}$ disturbance rejection attenuation level can be guaranteed for the estimation disagreement of the filtering network. Finally, simulation examples are provided to demonstrate the effectiveness of the theoretical results.
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