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Recursive subspace identification with prior information using the constrained least squares approach
Faculty
Not Specified
Year:
2013
Type of Publication:
Article
Pages:
174-180
Authors:
Alenany, Ahmed, Shang, Helen
DOI:
10.1016/j.compchemeng.2013.03.016
Journal:
COMPUTERS \& CHEMICAL ENGINEERING PERGAMON-ELSEVIER SCIENCE LTD
Volume:
54
Research Area:
Computer Science; Engineering
ISSN
ISI:000318979400017
Keywords :
Linear systems, System identification, Adaptive control
Abstract:
It is essential to develop high quality models for process control and other applications. The incorporation of prior information in subspace identification has been investigated to obtain improved model quality. One of the recent developments incorporates the prior information using the constrained least squares (CLS). In many online applications, the amount of process data for model identification grows with time, and it is therefore necessary to develop a recursive algorithm for online identification of process models and to address the time-varying characteristics of the systems. In this paper, a recursive subspace identification algorithm incorporating prior information is developed using the constrained recursive least squares (CRLS). It is shown via a simulation example that the state space model identified using the proposed algorithm possesses improved accuracy. (C) 2013 Elsevier Ltd. All rights reserved.
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