Protocol-based distributed finite-time estimation for two-time-scale sensor networks under communication constraints
摘要
This paper investigates the distributed state estimation problem for switched two-time-scale sensor networks, where measurements are transmitted to local estimators for information exchange over two distinct bandwidth-constrained communication channels. To mitigate data conflicts and alleviate the communication burden, a novel delay-dependent stochastic communication protocol (SCP) is proposed to schedule the measurement data, which is incorporated with a mixed compensation algorithm to establish a measurement model that closely approximates the actual value. Moreover, an innovative dynamic event-triggered strategy (ETS) is devised to optimize the transmissions of information between a single estimator node and its adjacent nodes and to effectively reduce the consumption of communication capacity, while the composite impact of dynamic ETS, DoS attacks and FDI attacks on signal transmission is integrated into a unified framework for better modelling the engineering practice. Subsequently, the mode-dependent distributed estimators are designed on the premise of a merging technique to amalgamate two Markov chains to ensure that the resulting augmented system is mean-square