SUBSPACE-BASED IDENTIFICATION METHODS USING SCHUR COMPLEMENT APPROACH

摘要

This paper shows a new interpretation of the subspace-based identification methods by using Schur complement approach. MOESP (MIMO output error state space model identification) algorithms are considered. Instead of the data matrices, we start to consider a data product moment consisted of the Hankel matrices of input-output data. It is shown that the instrumental variables (Ⅳ) extensions of data matrices in the MOESP can be expressed as modifications of the data product moment. It enables us to treat the Ⅳ-MOESP algorithms under a unified framework, and we also show that the interpretation can be applicable to the errors-in-variables (EIV) problems and the framework still can be kept.