Dynamic edge-event-based consensus of nonlinear multi-agent systems with sampled-data measurement

This paper investigates the leader-following consensus problem for a class of nonlinear multi-agent systems (MASs) by developing a novel edge-event-triggered control framework. To alleviate communication burdens, an edge-based triggering strategy is employed, wherein both the control protocols and triggering conditions depend exclusively on local relative information, eliminating the reliance on global network knowledge. Recognizing the constraints of practical communication scenarios, asynchronous information interactions across different edges are explicitly considered. As a core contribution, we seamlessly integrate sampled-data measurements with the edge-triggering paradigm, proposing a sampled-data edge-event triggered mechanism. This framework fundamentally circumvents the stringent requirement of continuous state monitoring and intrinsically excludes Zeno behavior, thereby significantly saving computational and communication resources. Furthermore, the framework is extended to a dynamic sampled-data-based edge-event-triggered mechanism, which introduces an auxiliary variable to provide greater flexibility in communication scheduling. Finally, the effectiveness and superiority of the proposed methods are demonstrated through an application example and comparative simulations.