Abstract
In this paper, a unified approach for subspace-based identification methods by using Schur complement is proposed. MOESP (MIMO output error state space model identification) type of subspace idenitification methods are well known as an elementary subspace method. The extensions of the MOESP with instrumental variables (IV) have been proposed, which can be useful to solve the stochastic identification problems. We consider data product moments corresponding to the data matrix in the MOESP algorithms, then we show that the IV matrices in the MOESP-based methods can be expressed as modifications of the data product moment, and it enable us to treat the IV-MOESP algorithms under a unified framework even if the errors-in-variables (EIV) problems are considered.
