State of the art in linear system identification: time and frequency domain methods

Abstract

Identification of time-invariant linear dynamic systems is a mature subject. In this contribution we focus on the interplay between methods that use time and frequency domain data, respectively. The frequency domain data could be either input/output Fourier transforms or frequency functions. We explain how these different kinds of data types are used to fit models, and how closely related the methods are. Of special interest is how transients (initial conditions and deviations from periodic signals) are handled. Direct estimation of time-continuous models is also discussed, as well as software aspects.