Data-driven Structured Realization

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Author(s) : Philipp Schulze , Benjamin Unger , Christopher Beattie , Serkan Gugercin

Preprint series of the Institute of Mathematics, Technische Universität Berlin
Preprint 23-2016

MSC 2000

93B15 Realizations from input-output data
30E05 Moment problems, interpolation problems

Abstract :
We present a framework for constructing structured realizations of linear dynamical systems having transfer functions of the form $C(\sum_{k=1}^K h_k(s)A_k)^{-1}B$ where $h_1, h_2, ..., h_K$ 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.

Keywords : structured realization, data-driven model reduction, interpolation, delay system, second-order system