Closed-loop subspace identification using the parity space

Authors:
Jin Wang;S. Joe Qin
Affiliations:
Advanced Process Control, Advanced Micro Devices, Inc. Austin, TX 78741, USA;Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
Venue:
Automatica (Journal of IFAC)
Year:
2006

Citing 11
Cited 1

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Consistency analysis of some closed-loop subspace identification methods

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Brief paper: Subspace aided data-driven design of robust fault detection and isolation systems

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Abstract

It is known that many subspace algorithms give biased estimates for closed-loop data due to the existence of feedback. In this paper we present a new subspace identification method using the parity space employed in fault detection in the past. The basic algorithm, known as subspace identification method via principal component analysis (SIMPCA), gives consistent estimation of the deterministic part and stochastic part of the system under closed loop. Column weighting for SIMPCA is introduced which shows improved efficiency/accuracy. A simulation example is given to illustrate the performance of the proposed algorithm in closed-loop identification and the effect of column weighting.