Data-Driven Event-Triggered Bipartite Consensus for Multi-Agent Systems Preventing DoS Attacks
Authors: Zhao, H., Shan, J., Peng, L. and Yu, H.
Journal: IEEE Control Systems Letters
Volume: 7
Pages: 1915-1920
eISSN: 2475-1456
DOI: 10.1109/LCSYS.2023.3281894
Abstract:This letter considers event-triggered bipartite consensus issues for discrete-time nonlinear networked multi-agent systems with antagonistic interactions and denial-of-service (DoS) attacks. Firstly, a pseudo partial derivative technology is applied to obtain an equivalent dynamic linearization model of the controlled system. The signed graph theory is employed to analyze the coopetition relationships among agents. Next, a distributed combined measurement error function is formulated to transform the bipartite consensus issue into a consensus issue. Then, an output predictive compensation scheme is proposed to offset the influence of DoS attacks. Furthermore, a dead-zone operator is designed to improve the flexibility of the proposed event-triggered mechanism. Additionally, a data-driven event-triggered resilient bipartite consensus scheme is formulated. Then, the convergence of the proposed method is strictly proved by using the Lyapunov theory and the contraction mapping principle, indicating that the bipartite consensus error could be reducing to a small region around zero. Finally, hardware tasks are conducted to verify the effectiveness of the proposed method.
Source: Scopus