Event-Triggered Control for Human-in-the-Loop Multi-agent Systems under DoS Attacks

This paper introduces an event-triggered secure control scheme for human-in-the-loop multi-agent systems in the context of DoS attacks. The integration of human intelligence and decision-making significantly enhances system security, as a human provides command signals to a non-autonomous leader agent. To determine unknown states, an adaptive neural state observer utilizes neural networks to approximate nonlinear functions, while a relative threshold-based event-triggered con-trol strategy is introduced to optimize communication resource usage. At the same time, a predictor is developed to monitor potential compromises in the edges of the multi-agent network to counteract attacks. Using Lyapunov analysis, it is shown that the proposed secure control protocol is capable of maintaining bounded closed-loop signals despite the occurrence of attacks. Finally, the effectiveness of the proposed scheme is validated by the simulation results.