# Robust Dynamic Event-Triggered Coordination With a Designable Minimum Inter-Event Time

## TL;DR

This paper introduces a fully distributed, robust, dynamic event-triggered algorithm for multi-agent consensus that guarantees a positive minimum inter-event time, addressing Zeno behavior and robustness issues present in prior methods.

## Contribution

It proposes the first fully distributed and robust dynamic event-triggered control strategy with a designable minimum inter-event time for directed networks.

## Key findings

- Guarantees a positive minimum inter-event time for each agent.
- Ensures non-Zeno behavior and robustness against disturbances.
- Applicable to general directed communication networks.

## Abstract

This paper revisits the classical multi-agent average consensus problem for which many different event-triggered control strategies have been proposed over the last decade. Many of the earliest versions of these works conclude asymptotic stability without proving that Zeno behavior, or deadlocks, do not occur along the trajectories of the system. More recent works that resolve this issue either: (i) propose the use of a dwell-time that forces inter-event times to be lower-bounded away from zero but sacrifice asymptotic convergence in exchange for practical convergence (or convergence to a neighborhood); (ii) guarantee non-Zeno behaviors and asymptotic convergence but do not provide a positive minimum inter-event time guarantee; or (iii) are not fully distributed. Additionally, the overwhelming majority of these works provide no form of robustness analysis on the event-triggering strategy. More specifically, if arbitrarily small disturbances can remove the non-Zeno property then the theoretically correct algorithm may not actually be implementable. Instead, this work for the first time presents a fully distributed, robust, dynamic event-triggered algorithm, for general directed communication networks, for which a desired positive minimum inter-event time can be chosen by each agent in a distributed fashion. Simulations illustrate our results.