Optimal and Approximate Solutions to Linear Quadratic Regulation of a Class of Graphon Dynamical Systems

TL;DR

This paper develops optimal and approximate control solutions for large-scale networked dynamical systems modeled by graphons, enabling scalable regulation with low complexity through spectral methods and Riccati equations.

Contribution

It introduces a novel spectral approach to solve LQR problems on graphon systems, including explicit solutions for finite spectral cases and low-complexity approximations for general couplings.

Findings

Explicit solutions for systems with finite spectral graphons.

Low-complexity suboptimal control via spectral approximations.

Numerical example demonstrating solution simplicity and effectiveness.

Abstract

In this paper we study the linear quadratic regulation (LQR) problem for dynamical systems coupled over large-scale networks and obtain locally computable low-complexity solutions. The underlying large or even infinite networks are represented by graphons and the couplings appear in both the dynamics and the quadratic cost. The optimal solution is obtained first for graphon dynamical systems for the special case where the graphons are exactly characterized by finite spectral summands. The complexity of generating these control solutions involves solving d+1 scalar Riccati equations where d is the number of non-zero eigenvalues in the spectral representation. Based on this, we provide a suboptimal low-complexity solution for problems with general graphon couplings via spectral approximations and analyze the performance under the approximate control. Finally, a numerical example is given to illustrate the explicit solution and demonstrate the simplicity of the solution.