H_infty Performance Analysis and Controller Design for Data-Driven Dynamic Event-Triggered Systems

This article is concerned with
$\mathbf{H}_{\infty}$
performance analysis and controller design for the dynamic event-triggered systems through noisy input-state data. A novel dynamic event-triggered scheme is proposed. Based on a data-driven representation, a new data-based analysis method for
$\mathbf{H}_{\infty}$
performance of the dynamic event-triggered system is introduced by using Lyapunov stability theorem, which relies on the noisy data rather than the model parameters. Beyond that, a data-based method for co-designing the
$\mathbf{H}_{\infty}$
controller and the event-triggering matrix is provided, through which the controller gain matrix can be optimized. Finally, a numerical example is given to illustrate the effectiveness of the proposed methods.