Secure Consensus of Multiagent Systems Under Replay Attacks: An Adaptive Parallel-Triggering Asynchronous Control Strategy.

This article addresses the secure consensus problem of Takagi-Sugeno (T-S) fuzzy multiagent systems (MASs) under replay attacks through event-based asynchronous control. Different from the existing research on event-triggered schemes (ETSs), a novel adaptive parallel-triggering strategy is designed to efficiently utilize limited network bandwidth and flexibly cope with system state changes. To deal with cybersecurity threats and complex nonlinear problems, a novel security consensus model for MASs under replay attacks based on the T-S fuzzy model is proposed. Then, the concern of asynchronous premise variables is addressed. Theoretical foundations are established via Lyapunov-Krasovskii-based stability analysis, yielding a set of verifiable secure control criteria that guarantee leader-following consensus under replay attacks. Comparative numerical simulations demonstrate the proposed method's superiority over conventional triggering schemes in both security performance and resource efficiency, validating the theoretical advancements.