Frequency-domain stable state-space system identification

Abstract

Due to possible distortion contained in frequency-domain data, system identification methods based on data-matching alone do not guarantee stable models. This is a model of a linear system from its frequency response data. It is an improvement and an extension of previous work. The method first identifies a matrix-fraction description of the transfer function matrix of the system from data. Then, through forming a multivariable observable or controllable canonical form, the method separates and replaces the unstable subsystem by a stable subsystem having approximately the same frequency response. Finally, it calculates the Markov parameters of the resulting model and obtains a state-space model through the Eigensystem Realization Algorithm.