Sampled-Data-Based Event-Triggered Synchronization Strategy for Directed Networks With Intermittent Communication Control

This research explores the synchronization problem in directed networks (DNs) under an intermittent communication controller, employing an event-triggered transmission technique that relies on sampling data. Upon analyzing the prior relevant results, it was observed that the derived synchronization conditions are closely related to the number of nodes in networks, reflecting the increasing computational complexity as the number of nodes grows, which makes obtaining a solution within a finite time challenging. To overcome this difficulty, this paper designs a novel intermittent controller and establishes a piecewise time-dependent Lyapunov-Krasovskii functional (PTDLKF) predicated on work and rest intervals of operation for the synchronization system. Next, an event-triggered synchronization method based on sampling data is explored to derive sufficient conditions that ensure asymptotic convergence of synchronization errors in the intermittent context. Importantly, the verification of matrix conditions in the established synchronization criterion is not contingent on the node count in networks. Finally, two simulation examples are provided to substantiate the applicability of the formulated synchronization method in the intermittent communication