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We introduce the Vector Fitting algorithm for the creation of reduced order models from the sampled response of a linear time-invariant system. This datadriven approach to reduction is particularly useful when the system under modeling is known only through experimental measurements. The theory behind Vector Fitting is presented for single- and multiple-input systems, together with numerical details, pseudo-codes, and an open-source implementation [75]. We discuss how the reduced model can be made stable and converted to a variety of forms for use in virtually any modeling context. Finally, we survey recent extensions of the Vector Fitting algorithm geared towards time domain, parametric and distributed systems modeling.

© 2021 Walter de Gruyter GmbH, Berlin/Munich/Boston
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