Data-Driven Model Reduction by Moment Matching for Linear Systems through a Swapped Interconnection

In this work, we propose a time-domain data-driven technique for model reduction by moment matching of linear systems. We propose an algorithm, based on the so-called swapped interconnection, that (asymptotically) approximates an arbitrary number of moments of the system from a single time-domain sample. A family of reduced-order models that match the estimated moments is derived. Finally, the use of the proposed algorithm is demonstrated on the problem of model reduction of a building model.