Computing delay Lyapunov matrices and H2 norms for large-scale problems

TL;DR

This paper introduces a novel scalable method for computing delay Lyapunov matrices and H2 norms in large-scale delay differential systems, leveraging spectral discretization, structure-preserving transformations, and Krylov subspace techniques.

Contribution

The authors develop a new approach that avoids direct boundary value problem solutions, enabling efficient computation for large, sparse systems with low-rank right-hand sides.

Findings

Method efficiently computes delay Lyapunov matrices for large systems.

Algorithm exploits problem structure for improved accuracy and sparsity.

Numerical experiments demonstrate effectiveness and scalability.

Abstract

A delay Lyapunov matrix corresponding to an exponentially stable system of linear time-invariant delay differential equations can be characterized as the solution of a boundary value problem involving a matrix valued delay differential equation. This boundary value problem can be seen as a natural generalization of the classical Lyapunov matrix equation. We present a general approach for computing delay Lyapunov matrices and H2 norms for systems with multiple discrete delays, whose applicability extends towards problems where the matrices are large and sparse, and the associated positive semidefinite matrix (the ``right-hand side' for the standard Lyapunov equation), has a low rank. In contract to existing methods that are based on solving the boundary value problem directly, our method is grounded in solving standard Lyapunov equations of increased dimensions. It combines several ingredients: i) a spectral discretization of the system of delay equations, ii) a targeted similarity transformation which induces a desired structure and sparsity pattern and, at the same time, favors accurate low rank solutions of the corresponding Lyapunov equation, and iii) a Krylov method for large-scale matrix Lyapunov equations. The structure of the problem is exploited in such a way that the final algorithm does not involve a preliminary discretization step, and provides a fully dynamic construction of approximations of increasing rank. Interpretations in terms of a projection method directly applied to a standard linear infinite-dimensional system equivalent to the original time-delay system are also given. Throughout the paper two didactic examples are used to illustrate the properties of the problem, the challenges and methodological choices, while numerical experiments are presented at the end to illustrate the effectiveness of the algorithm.