Resource-Efficient Adaptive Tracking for Uncertain Multi-Agent Networks via Layered Event-Driven Architecture

This paper presents a novel dual event-driven hierarchical control architecture to achieve fully distributed practical prescribed-time consensus (Pd-TC) tracking for uncertain multi-agent systems (MASs). Firstly, a distributed estimate layer is established to reconstruct the leader’s states, guaranteeing practical prescribed-time convergence of estimation errors independent of global information. The proposed communication-triggered event-triggered mechanism (ETM) eliminates continuous communication among neighboring followers, effectively reducing communication resource consumption. Then, utilizing the estimated information, a local control layer is designed to realize practical Pd-TC tracking for uncertain MASs, where the control-update ETM reduces unnecessary control updates to conserve limited control resources, and adaptive gains eliminate the dependence on the bounds of disturbances and uncertain inherent parameters. Furthermore, a rigorous analysis confirms the exclusion of Zeno behavior in both communication-triggered and control-update ETMs. Finally, the proposed control architecture is applied to multiple ground vehicles, validating the theoretical findings.