Data-driven Control of Dynamic Event-triggered Systems with Delays

TL;DR

This paper introduces a data-driven approach for controlling unknown sampled-data systems with delays using event-triggered mechanisms, providing stability conditions and co-design methods that improve efficiency and reduce conservatism.

Contribution

It develops data-based representations and stability conditions for event-triggered control of delayed systems, including co-design methods with or without known input matrices.

Findings

Data-driven stability conditions are effective for unknown systems.

Prior knowledge of input matrices reduces conservatism.

Proposed schemes outperform existing methods in numerical examples.

Abstract

This paper studies data-driven control of unknown sampled-data systems with communication delays under an event-triggering transmission mechanism. Data-based representations for time-invariant linear systems with known or unknown system input matrices are first developed, along with a novel class of dynamic triggering schemes for sampled-data systems with time delays. A model-based stability condition for the resulting event-triggered time-delay system is established using a looped-functional approach. Combining this model-based condition with the data-driven representations, data-based stability conditions are derived. Building on the data-based conditions, methods for co-designing the controller gain and the event-triggering matrix are subsequently provided for both cases with or without using the input matrix. Finally, numerical examples are presented to corroborate the usefulness of additional prior knowledge of the input matrix in reducing the conservatism of stability conditions, as well as the merits of the proposed data-driven event-triggered control schemes relative to existing results.