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

초록

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. Note to Practitioners-Many cooperative control tasks, such as ground vehicle formation, can be modeled as consensus tracking problems for resource-constrained MASs. The proposed dual event-driven hierarchical control architecture for Pd-TC tracking employs a single tunable parameter to determine the settling time, which offers advantages over finite-time and fixed-time schemes and facilitates practical engineering implementation. Under this architecture, the distributed tracking problem is decomposed into distributed estimation and local tracking control. A fully distributed event-triggered observer is established to eliminate continuous communication among neighboring followers while ensuring practical prescribed-time convergence of estimation errors. Then, an adaptive controller with a control-update ETM is designed to reduce update frequency while ensuring practical Pd-TC tracking for uncertain MASs. The proposed hierarchical control architecture can also be applied to smart grids and sensor networks.

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