  The present paper deals with data-driven event-triggered control of a class
of unknown discrete-time interconnected systems (a.k.a. network systems). To
this end, we start by putting forth a novel distributed event-triggering
transmission strategy based on periodic sampling, under which a model-based
stability criterion for the closed-loop network system is derived, by
leveraging a discrete-time looped-functional approach. Marrying the model-based
criterion with a data-driven system representation recently developed in the
literature, a purely data-driven stability criterion expressed in the form of
linear matrix inequalities (LMIs) is established. Meanwhile, the data-driven
stability criterion suggests a means for co-designing the event-triggering
coefficient matrix and the feedback control gain matrix using only some offline
collected state-input data. Finally, numerical results corroborate the efficacy
of the proposed distributed data-driven ETS in cutting off data transmissions
and the co-design procedure.
