Data-Driven Control of Distributed Event-Triggered Network Systems

TL;DR

This paper introduces a novel data-driven event-triggered control method for unknown network systems, enabling stability analysis and controller design solely from offline data, reducing communication load.

Contribution

It develops a distributed data-driven stability criterion and co-design approach for event-triggered control in network systems using LMIs and offline data.

Findings

The proposed method effectively reduces data transmissions.

The co-design approach achieves stable control with offline data.

Numerical results validate the method's efficacy.

Abstract

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.