LAUSR

We investigate the dynamic event-triggered state estimation for uncertain complex networks with hybrid delays suffering from both deception attacks and denial-of-service attacks. Firstly, the effects of time-varying delays and finitedistributed delays are considered during data transmission between nodes. Secondly, a dynamic event-triggered scheme (ETS) is introduced to reduce the frequency of data transmission between sensors and estimators. Thirdly, by considering the discussed plant, dynamic ETS, state estimator, and hybrid attacks into a unified framework, this framework is transferred into a novel dynamical model. Furthermore, with the help of Lyapunov stability theory and linear matrix inequality techniques, sufficient condition to ensure that the system is exponentially stable and satisfies H∞ performance constraints is obtained, and the design algorithm for estimator gains is given. Finally, two numerical examples verify the effectiveness of the proposed method.