Snapshot-driven Rational Interpolation of Parametric Systems
Published in arXiv, 2024
Parametric data-driven modeling is relevant for many applications in which the model depends on parameters that can potentially vary in both space and time. In this paper, we present a method to obtain a global parametric model based on snapshots of the parameter space. The parameter snapshots are interpolated using the classical univariate Loewner framework and the global bivariate transfer function is extracted using a linear fractional transformation (LFT). Rank bounds for the minimal order of the global realization are also derived. The results are supported by various numerical examples.
Recommended citation: Pelling, A.J.R. et al. (2024) “Snapshot-driven Rational Interpolation of Parametric Systems.” arXiv. Available at: https://doi.org/10.48550/arXiv.2406.01236.
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