Data-driven structured realization

We present a framework for constructing structured realizations of linear dynamical systems having transfer functions of the form C̃(∑_k=1^K h_k(s)Ã_k)^-1B̃ where h₁, h₂, ..., 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.