Adaptive consensus-based distributed H∞ filtering with switching topology subject to partial information on transition probabilities

This article is dedicated to designing distributed state estimators for time-varying delay systems. The filtering network communication topology is time-varying, and it is presumed that the switching mechanism follows a homogeneous Markov chain, with partially unknown information in the probability transition matrix. An adaptive event-triggered mechanism is embedded in the sensor network, which reduces unnecessary communication data and saves communication resources. By utilising the mode-dependent Lyapunov function, sufficient conditions are deduced to ensure the H-infinity-consensus performance for the filtering error dynamics. Then, some intensive analysis is performed to obtain the explicit expressions of the distributed H-infinity state estimator by introducing slack variables and free-connection weighting matrices. Finally, two numerical simulations are proposed to demonstrate the effectiveness of theoretical results. (C) 2021 Elsevier Inc. All rights reserved.