Abstract
In this paper, we present a new interpretation of the subspace-based state space system identification (4SID) method by using a subspace extraction via Schur complement (SES). Several efficient implementations of subspace-based identification methods (e.g., N4SID, etc) have been thus far developed and proposed. We consider the MIMO output error state space model identification, the so-called MOESP. Making a comparison between the matrix obtained by the QR factorization in the MOESP and the Schur complement matrix of data product moments shows that the estimate of the extended observability matrix can be obtained by using the SES procedure. Viewing that fact that the Schur complement yielded by the subspace extraction coincides with the error covariance in the least squares (LS), our interpretation will pave the way for the derivation of the recursive algorithm of the 4SID method.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IEEE Conference on Decision and Control |
| Pages | 3924-3929 |
| Number of pages | 6 |
| Volume | 4 |
| Publication status | Published - 2001 |
| Externally published | Yes |
| Event | 40th IEEE Conference on Decision and Control (CDC) - Orlando, FL, United States Duration: Dec 4 2001 → Dec 7 2001 |
Other
| Other | 40th IEEE Conference on Decision and Control (CDC) |
|---|---|
| Country | United States |
| City | Orlando, FL |
| Period | 12/4/01 → 12/7/01 |
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ASJC Scopus subject areas
- Chemical Health and Safety
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality
Cite this
A new interpretation of subspace methods by using Schur complement. / Takei, Yoshinori; Imai, Jun; Wada, Kiyoshi.
Proceedings of the IEEE Conference on Decision and Control. Vol. 4 2001. p. 3924-3929.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A new interpretation of subspace methods by using Schur complement
AU - Takei, Yoshinori
AU - Imai, Jun
AU - Wada, Kiyoshi
PY - 2001
Y1 - 2001
N2 - In this paper, we present a new interpretation of the subspace-based state space system identification (4SID) method by using a subspace extraction via Schur complement (SES). Several efficient implementations of subspace-based identification methods (e.g., N4SID, etc) have been thus far developed and proposed. We consider the MIMO output error state space model identification, the so-called MOESP. Making a comparison between the matrix obtained by the QR factorization in the MOESP and the Schur complement matrix of data product moments shows that the estimate of the extended observability matrix can be obtained by using the SES procedure. Viewing that fact that the Schur complement yielded by the subspace extraction coincides with the error covariance in the least squares (LS), our interpretation will pave the way for the derivation of the recursive algorithm of the 4SID method.
AB - In this paper, we present a new interpretation of the subspace-based state space system identification (4SID) method by using a subspace extraction via Schur complement (SES). Several efficient implementations of subspace-based identification methods (e.g., N4SID, etc) have been thus far developed and proposed. We consider the MIMO output error state space model identification, the so-called MOESP. Making a comparison between the matrix obtained by the QR factorization in the MOESP and the Schur complement matrix of data product moments shows that the estimate of the extended observability matrix can be obtained by using the SES procedure. Viewing that fact that the Schur complement yielded by the subspace extraction coincides with the error covariance in the least squares (LS), our interpretation will pave the way for the derivation of the recursive algorithm of the 4SID method.
UR - http://www.scopus.com/inward/record.url?scp=0035711072&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0035711072&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0035711072
VL - 4
SP - 3924
EP - 3929
BT - Proceedings of the IEEE Conference on Decision and Control
ER -