Dynamic Event-Triggered Consensus Tracking Control for Nonlinear Stochastic Multi-Agent Systems Under Dual Network Attacks

Abstract

This study discusses consensus tracking control problems for nonlinear stochastic multi-agent systems under DoS attacks and deception attacks. The above attacks are respectively described as receiving duplicate data and receiving false data. In an effort to save network resources, this study proposes an appropriate dynamic event-triggered mechanism. On this basis, a feedback controller for consensus tracking is designed. Then, a new consensus tracking criterion under dual network attacks is proposed. In addition, by selecting a new Lyapunov–Krasovskii functional and using Jesen inequality, sufficient conditions for system mean-square stability are obtained. Finally, the efficacy of this approach is validated through a numerical example.