State saturated recursive filtering for nonlinear complex networks with energy harvesting sensors and false data injection attacks

Summary The state saturated recursive filtering issue is researched in this article for nonlinear complex networks with energy harvesting sensors and false data injection (FDI) attacks. In communication networks, the energy of the sensors is used to transmit data from sensors to remote filters. Due to ample energy being a prerequisite for the transmission of data, the energy harvesting technology is provided. During the process of data transmission, the measurement signals may be attacked by the false data. Thereinto, the Bernoulli random variables are used to depict FDI attacks. The primary goal is to devise a filter that minimizes the upper bound for the filtering error covariance. Subsequently, a discussion is shown for the proposed filtering bounded analysis for the filtering error. Finally, a numerical simulation experiment is carried out to demonstrate the applicability and effectiveness for the proposed novel filtering algorithm.