Distributed Filtering for State-Saturated Systems With Switching Nonlinearities via Rayleigh Fading Channels: An Adaptive Event-Triggered Case

The distributed filtering (DF) problem is investigated for state-saturated systems (SSSs) with switching nonlinearities under the adaptive event-triggered mechanism (AETM) and Rayleigh fading channels over sensor networks, where the data is transmitted between nodes through the Rayleigh fading channel. In addition, the AETM is introduced to save communication resources and improve data transmission efficiency. First, a distributed filter is designed incorporating the information of state saturation, switching nonlinearity, Rayleigh fading channel and AETM. Second, the upper bound (UB) on the filtering error covariance (FEC) is derived by the mathematical induction method, and the filter gain is obtained by minimizing the trace of the UB. Subsequently, the boundedness of UB on the FEC is shown through mathematical analysis. Finally, the effectiveness of the filtering scheme designed in this article is demonstrated through a numerical simulation example and a practical example, in which the influence of different Rayleigh parameters to the filtering performance and the superiority of using the AETM are discussed.