ABSTRACT
This paper presents an event-triggered distributed control protocol designed for scenarios involving Denial-of-Service (DoS) attacks within directed communication graphs. We address the consensus problem of uncertain systems by employing neural networks to approximate nonlinear components. Compared with traditional neural network observers, the proposed method incorporates damping terms to ensure the boundedness of neural network estimators. Initially, an auxiliary system was constructed to decouple the consensus problem under a directed communication graph framework. It is demonstrated that the uncertain nonlinear system can achieve consensus through the utilization of information exchanged among neighboring agents. Subsequently, to curtail the consumption of communication resources, we introduce an event-triggered control protocol based on the aforementioned approach, incorporating an effective event-triggering function. Building upon the proposed control protocol, we further develop a control strategy tailored for systems under DoS attacks. Furthermore, the event-triggered mechanism without using global information in trigger condition not only curtails superfluous information exchange among agents but also precludes the occurrence of Zeno behavior (i.e., infinite triggering within a finite time interval). Finally, numerical simulations are carried out to validate the efficacy of the proposed control protocol.
International Journal of Robust and Nonlinear Control, EarlyView. Read More
