Orchestrated Couplings: A Time-Varying Edge Weight Framework for Efficient Event-Triggered Multiagent Networks

TL;DR

This paper introduces a novel time-varying edge weight event-triggered control framework for multiagent networks that reduces communication events and enhances performance by dynamically adjusting edge weights during different network phases.

Contribution

It proposes a new framework that dynamically adjusts edge weights in multiagent networks, improving efficiency and performance over existing static methods.

Findings

Reduces number of communication events in the network.

Improves convergence speed and control effort.

Proves stability and absence of Zeno behavior.

Abstract

In this paper, we focus on reducing node-to-node information exchange in distributed control of multiagent networks while improving the overall network performance. Specifically, we consider a multiagent network that is composed of leader and follower nodes over a time-varying, connected, and undirected graph. In contrast to existing works on the event-triggered distributed control literature, we propose a time-varying edge weight event-triggered control framework. In this framework, each node dynamically adjusts its edge weights by increasing them during the transient (active) phase and decreasing them during the steady-state (idle) phase of the multiagent network. This not only reduces the number of events in the network but also improves the performance (i.e., convergence speed and control effort) of the overall multiagent network. System-theoretically, we first prove the closed-loop stability of the proposed event-triggered distributed control framework, where we then show that this framework does not exhibit a Zeno behavior. Finally, illustrative numerical examples are provided to demonstrate the efficacy of this framework.