Resilient Self/Event-Triggered Consensus Based on Ternary Control

TL;DR

This paper introduces a resilient multi-agent consensus method that combines ternary control with self- and event-triggered communication to enhance robustness and reduce communication in adversarial environments.

Contribution

It extends mean subsequence reduced algorithms by integrating ternary data exchange and self-/event-triggered communication for improved resilience and efficiency.

Findings

Self-triggered approach offers advantages over event-triggered in hostile settings.

Reduced communication frequency without compromising consensus.

Enhanced robustness against adversarial agents.

Abstract

The paper considers the problem of multi-agent consensus in the presence of adversarial agents which may try to prevent and introduce undesired influence on the coordination among the regular agents. To our setting, we extend the so-called mean subsequence reduced algorithms with the aim to reduce the amount of communication via two measures: The agents exchange information in the form of ternary data at each transmission and moreover keep the frequency of data exchange low by employing self- and event-triggered communication. We will observe that in hostile environments with adversaries, the self-triggered approach can bring certain advantages over the event-triggered counterpart.