On the Ergodic Control of Ensembles

TL;DR

This paper examines the limitations of PI control in managing large ensembles of agents, highlighting potential ergodicity loss, and proposes a theoretical framework for analyzing and designing more effective control systems.

Contribution

It introduces a new theoretical framework for controlling large agent ensembles, addressing ergodicity issues overlooked by traditional PI control methods.

Findings

PI control may cause ergodicity loss in ensemble systems

A new framework for analyzing ensemble control systems is proposed

Examples demonstrate the effectiveness of the new approach

Abstract

Across smart-grid and smart-city application domains, there are many problems where an ensemble of agents is to be controlled such that both the aggregate behaviour and individual-level perception of the system's performance are acceptable. In many applications, traditional PI control is used to regulate aggregate ensemble performance. Our principal contribution in this note is to demonstrate that PI control may not be always suitable for this purpose, and in some situations may lead to a loss of ergodicity for closed-loop systems. Building on this observation, a theoretical framework is proposed to both analyse and design control systems for the regulation of large scale ensembles of agents with a probabilistic intent. Examples are given to illustrate our results.