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.
|Number of pages||6|
|Journal||IFAC Proceedings Volumes|
|Publication status||Published - Jul 2004|
|Event||7th IFAC Symposium on Dynamics and Control of Process Systems, DYCOPS 2004 - Cambridge, United States|
Duration: 5 Jul 2004 → 7 Jul 2004
Bibliographical noteSupported by NSF under CTS-9985074 and an Overseas Young Investigator Award (60228001) from NSF China.
- Closed-loop identification
- Consistency analysis
- Instrumental variables
- Parity space
- Principal component analysis
- Subspace identification