Reliable mixed H2/H∞ distributed estimation for periodic nonlinear systems with jumping topology

This paper investigates the problem of reliable mixed H2/H∞ distributed state estimation for periodic nonlinear systems. A sensor network with time-varying topology is used to measure the system, where the time-varying condition is described by a period index dependent Markov chain. A distributed state estimator is designed based on the local and neighbors’ innovation information of each node, while the non-fragile estimator is considered to improve the robustness of the estimator. An augmented estimation error system is derived, while the developed sufficient condition is carried out to ensure the stochastic stability and the mixed H2/H∞ performance. Then, the expected estimator gains are solved on the basis of the achieved sufficient condition. Finally, the effectiveness of the proposed state estimation method is emphasized by a numerical example and the comparative experiments.