Multivariable State-Space Identification in the Delta and Shift Operators

Abstract

This paper develops algorithms for multivariable state-space identification which can be used to estimate models in any operator of interest i.e., delta-rule, shift, Laplace s, etc. The approach is based on the State-Space from Frequency Data (SSFD) algorithm which was designed specifically to eliminate distortions from windowing effects.