Event‐Triggered State Estimation for Complex Networks With Switching Topologies Under Multiple Denial‐Of‐Service Attacks

ABSTRACT This article investigates the state estimation problem (SEP) for complex networks (CNs) with switching topologies subject to denial‐of‐service (DoS) attacks, utilizing an event‐triggering strategy to reduce data transmissions. It is noteworthy that DoS attacks may occur not only on topology channels but also on output channels. Different from previous works in which DoS attack behavior follows Bernoulli distribution, this article employs a more general deterministic DoS model. To achieve state estimation under these conditions, we develop an extended Kalman filter (EKF) that switches between two different dynamics and derive a piecewise Riccati‐like difference equation whose solution provides an upper bound matrix for the estimation error covariance (EEC). Subsequently, a criterion is established to ensure that the estimation error (EE) remains bounded in mean square in the presence of DoS. We derive a duty cycle for DoS attacks below which the boundedness of the EE is maintained. Finally, the effectiveness of our algorithm is certified by a simulation example.