Least Squares Model Reduction: A Two-Stage System-Theoretic Interpretation

Alberto Padoan

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arXiv · 2505.20604

Least Squares Model Reduction: A Two-Stage System-Theoretic Interpretation

Alberto Padoan

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Abstract

Model reduction simplifies complex dynamical systems while preserving essential properties. This paper revisits a recently proposed system-theoretic framework for least squares moment matching. It interprets least squares model reduction in terms of two steps process: constructing a surrogate model to satisfy interpolation constraints, then projecting it onto a reduced-order space. Using tools from output regulation theory and Krylov projections, this approach provides a new view on classical methods. For illustration, we reexamine the least-squares model reduction method by Lucas and Smith, offering new insights into its structure.

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BibTeX RIS

Alberto Padoan. 2025-05-27. Least Squares Model Reduction: A Two-Stage System-Theoretic Interpretation. https://arxiv.org/abs/2505.20604

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