Data-Driven Control of Distributed Event-Triggered Network Systems

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.

13 pages, 8 figures

References in corpus (2)

• Combining Prior Knowledge and Data for Robust Controller Design
• Data-driven analysis and control of continuous-time systems under aperiodic sampling

Cited by in corpus (4)

• Model-Based and Data-Driven Control of Event- and Self-Triggered Discrete-Time LTI Systems
• Event-triggered Consensus Control of Heterogeneous Multi-agent Systems: Model- and Data-based Analysis
• Data-driven Control of Dynamic Event-triggered Systems with Delays
• Data-driven input-to-state stabilization with respect to measurement errors