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