On Distributed Internal Model Principle for Output Regulation over Time-Varying Networks of Linear Heterogeneous Agents

TL;DR

This paper develops a distributed control strategy for multi-agent systems with heterogeneous dynamics, enabling output regulation over time-varying networks by extending the internal model principle to a networked setting.

Contribution

It introduces a novel distributed controller combining exosystem generation and internal model consensus for heterogeneous agents with uncertain dynamics.

Findings

Successfully achieves output regulation in heterogeneous multi-agent systems.

Handles time-varying directed networks with consensus-based methods.

Extends internal model principle to distributed, networked systems.

Abstract

We study a multi-agent output regulation problem, where not all agents have access to the exosystem's dynamics. We propose a distributed controller that solves the problem for linear, heterogeneous, and uncertain agent dynamics as well as time-varying directed networks. The distributed controller consists of two parts: (1) an exosystem generator that creates a local copy of the exosystem dynamics by using consensus protocols, and (2) a dynamic compensator that uses (again) consensus to approach the internal model of the exosystem and thereby achieves perfect output regulation. Our approach leverages methods from internal model based controller synthesis, multi-agent consensus over directed networks, and stability of time-varying linear systems; the derived result is an adaptation of the (centralized) internal model principle to the distributed, networked setting.