Neural networks-based event-triggered consensus control for nonlinear multiagent systems with communication link faults and DoS attacks

Abstract

This paper investigates the consensus control problem for a class of nonlinear multi-agent systems (MASs) with communication link faults and denial-of-service (DoS) attacks. First, considering simultaneously the communication link faults and DoS attacks, an adaptive event-triggered control strategy of MASs is proposed based on distributed adjacency error signals, and the avoidance of the Zeno phenomenon is analyzed. In addition, the unknown nonlinear functions can be approximated by the RBF neural networks. Then, based on Lyapunov stability analysis and induction, it is proved that all signals of MASs are uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed control scheme is verified by a simulation example.

Keywords

• neural networks
• event-triggered
• multi-agent systems
• communication link faults
• dos attacks