Subspace Identification Using the Parity Space

Jin WANG; S. Joe QIN

doi:10.1016/S1474-6670(17)31825-6

Subspace Identification Using the Parity Space

Jin WANG, S. Joe QIN

Research output: Journal Publications › Journal Article (refereed) › peer-review

1 Citation (Scopus)

Abstract

It is known that most subspace identification algorithms give biased estimates for closed-loop data due to a projection performed in the algorithms. In this work, consistency analysis of SIMPCA is given and the exact input requirement is formulated. The effect of column weighting in subspace identification algorithms is discussed and the column weighting for SIMPCA is designed which gives consistent estimates of state-space models from both open loop and closed-loop data. A simulation example is given to demonstrate the performance of the proposed algorithm.

Original language	English
Pages (from-to)	287-292
Number of pages	6
Journal	IFAC Proceedings Volumes
Volume	37
Issue number	9
DOIs	https://doi.org/10.1016/S1474-6670(17)31825-6
Publication status	Published - Jul 2004
Externally published	Yes
Event	7th IFAC Symposium on Dynamics and Control of Process Systems, DYCOPS 2004 - Cambridge, United States Duration: 5 Jul 2004 → 7 Jul 2004

Bibliographical note

Supported by NSF under CTS-9985074 and an Overseas Young Investigator Award (60228001) from NSF China.

Keywords

Closed-loop identification
Consistency analysis
Instrumental variables
Parity space
Principal component analysis
Subspace identification

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10.1016/S1474-6670(17)31825-6

Cite this

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title = "Subspace Identification Using the Parity Space",

abstract = "It is known that most subspace identification algorithms give biased estimates for closed-loop data due to a projection performed in the algorithms. In this work, consistency analysis of SIMPCA is given and the exact input requirement is formulated. The effect of column weighting in subspace identification algorithms is discussed and the column weighting for SIMPCA is designed which gives consistent estimates of state-space models from both open loop and closed-loop data. A simulation example is given to demonstrate the performance of the proposed algorithm.",

keywords = "Closed-loop identification, Consistency analysis, Instrumental variables, Parity space, Principal component analysis, Subspace identification",

author = "Jin WANG and QIN, {S. Joe}",

note = "Supported by NSF under CTS-9985074 and an Overseas Young Investigator Award (60228001) from NSF China.; 7th IFAC Symposium on Dynamics and Control of Process Systems, DYCOPS 2004 ; Conference date: 05-07-2004 Through 07-07-2004",

year = "2004",

month = jul,

doi = "10.1016/S1474-6670(17)31825-6",

language = "English",

volume = "37",

pages = "287--292",

journal = "IFAC Proceedings Volumes",

issn = "1474-6670",

publisher = "IFAC Secretariat",

number = "9",

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TY - JOUR

T1 - Subspace Identification Using the Parity Space

AU - WANG, Jin

AU - QIN, S. Joe

N1 - Supported by NSF under CTS-9985074 and an Overseas Young Investigator Award (60228001) from NSF China.

PY - 2004/7

Y1 - 2004/7

N2 - It is known that most subspace identification algorithms give biased estimates for closed-loop data due to a projection performed in the algorithms. In this work, consistency analysis of SIMPCA is given and the exact input requirement is formulated. The effect of column weighting in subspace identification algorithms is discussed and the column weighting for SIMPCA is designed which gives consistent estimates of state-space models from both open loop and closed-loop data. A simulation example is given to demonstrate the performance of the proposed algorithm.

AB - It is known that most subspace identification algorithms give biased estimates for closed-loop data due to a projection performed in the algorithms. In this work, consistency analysis of SIMPCA is given and the exact input requirement is formulated. The effect of column weighting in subspace identification algorithms is discussed and the column weighting for SIMPCA is designed which gives consistent estimates of state-space models from both open loop and closed-loop data. A simulation example is given to demonstrate the performance of the proposed algorithm.

KW - Closed-loop identification

KW - Consistency analysis

KW - Instrumental variables

KW - Parity space

KW - Principal component analysis

KW - Subspace identification

UR - http://www.scopus.com/inward/record.url?scp=85083268519&partnerID=8YFLogxK

U2 - 10.1016/S1474-6670(17)31825-6

DO - 10.1016/S1474-6670(17)31825-6

M3 - Journal Article (refereed)

SN - 1474-6670

VL - 37

SP - 287

EP - 292

JO - IFAC Proceedings Volumes

JF - IFAC Proceedings Volumes

IS - 9

T2 - 7th IFAC Symposium on Dynamics and Control of Process Systems, DYCOPS 2004

Y2 - 5 July 2004 through 7 July 2004

ER -

Subspace Identification Using the Parity Space

Abstract

Bibliographical note

Keywords

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