Partial-nodes-based state estimation for complex networks under hybrid attacks: a dynamic event-triggered approach
Zhou Lu, Jin Hu, Bing Li
Abstract
This article addresses the problem of state estimation for complex networks under hybrid cyber attacks. A hybrid model is constructed to encompass cyber attacks in both deception and denial-of-service (DoS) manners. A dynamic event-triggered mechanism (DETM) is brought into the channel between sensors and the estimator for deducing the transmission frequency. Our primary target is to develop an estimator capable of accurately assessing network states, relying on measurements from partially selected network nodes. Taking use of Lyapunov stability theory and stochastic analysis techniques, several criteria are formulated to guarantee the exponentially mean square ultimate boundedness (EMSUB) of the estimation error dynamics. The estimator gains are determined by resolving specific matrix inequalities. To illustrate the efficacy of our newly devised estimator design approach, a numerical example is provided along with corresponding simulations.