Data-driven Structured Realization
Systems and Control
2018-01-30 v1 Numerical Analysis
Abstract
We present a framework for constructing structured realizations of linear dynamical systems having transfer functions of the form where 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
Cite
@article{arxiv.1611.02072,
title = {Data-driven Structured Realization},
author = {Philipp Schulze and Benjamin Unger and Christopher Beattie and Serkan Gugercin},
journal= {arXiv preprint arXiv:1611.02072},
year = {2018}
}