Quantized control for a class of neural networks with adaptive event-triggered scheme and complex cyber-attacks

摘要

This article is concerned with the quantized control problem for neural networks with adaptive event-triggered scheme (AETS) and complex cyber-attacks. By fully considering the characteristics of cyber-attacks, a mathematical model of complex cyber-attacks, which consists of replay attacks, deception attacks, and denial-of-service (DoS) attacks, is firstly built for neural networks. For the sake of relieving the pressure under limited communication resources, an AETS and a quantization mechanism are employed in this article. By utilizing Lyapunov stability theory, adequate conditions ensuring the stability of neural networks are obtained. Moreover, the controller gain is derived by solving a set of linear matrix inequalities. At last, the usefulness of the proposed method is verified by a numerical example.