Data-driven Structured Realization
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Abstract (arXiv)
We present a framework for constructing structured realizations of linear dynamical systems having transfer functions of the form C(sumk=1K hk(s)Ak)-1B where h1,h2,ldots,hK are prescribed functions that specify the surmised structure of the model. Our construction is data-driven in the sense that an interpolant is derived entirely from measurements of a transfer function. Our approach extends the Loewner realization framework to more general system structure that includes second-order (and higher) systems as well as systems with internal delays. Numerical examples demonstrate the advantages of this approach.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Nov 2016.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 2; 2024: 2; 2025: 2; 2026: 1.
11 papers.
- 2021Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inferencecited by 16
- 2022On the sample complexity of stabilizing linear dynamical systems from datacited by 8
- 2021Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectoriescited by 5
- 2022Context-aware controller inference for stabilizing dynamical systems from scarce datacited by 3
- 2023Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemescited by 3
- 2024System stabilization with policy optimization on unstable latent manifoldscited by 2
- 2023Rank-Minimizing and Structured Model Inferencecited by 1
- 2026Nonlinear model reduction for transport-dominated problemscited by 1
- 2024Active Sampling of Interpolation Points to Identify Dominant Subspaces for Model Reductioncited by 0
- 2025An adaptive data sampling strategy for stabilizing dynamical systems via controller inferencecited by 0
- 2025Second-order AAA algorithms for structured data-driven modelingcited by 0
- 2026Nonlinear model reduction for transport-dominated problems1 Feb 2026
- 2025Second-order AAA algorithms for structured data-driven modeling2 Jun 2025
- 2025An adaptive data sampling strategy for stabilizing dynamical systems via controller inference2 Jun 2025
- 2024Active Sampling of Interpolation Points to Identify Dominant Subspaces for Model Reduction5 Sep 2024
- 2024System stabilization with policy optimization on unstable latent manifolds8 Jul 2024
- 2023Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemes11 Oct 2023
- 2023Rank-Minimizing and Structured Model Inference19 Feb 2023
- 2022Context-aware controller inference for stabilizing dynamical systems from scarce data22 Jul 2022
- 2022On the sample complexity of stabilizing linear dynamical systems from data28 Feb 2022
- 2021Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference6 Jul 2021
- 2021Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories1 Mar 2021