Event-triggered Model-Free Distributed tracking control for Networked Nonlinear multi-agent systems under communication delays

In this paper, an event-triggered distributed delay compensation tracking control strategy is proposed for networked nonlinear multi-agent systems with unknown dynamics and time-varying communication delays. First, to address the lack of system models, a data-driven control framework is established using compact-form dynamic linearization, which constructs a locally linearized model solely from the agent’s historical input-output data. Second, a fully decentralized event-triggered mechanism is designed, where each agent autonomously determines its control updates based on locally measured output errors, eliminating the need for continuous state information from neighboring agents. Third, integrated with a networked predictive compensation scheme, the proposed strategy actively mitigates time-varying round-trip delays by synchronizing predicted states with actual delayed measurements. The simulation results show that the proposed algorithm can effectively compensate for the delays and reduce the burden of network communication while ensuring the tracking performance of system output.