NDLI: Integrating Prior Information into Subspace Identification Methods

Content Provider	IEEE Xplore Digital Library
Author	Trnka, P. Havlena, V.
Copyright Year	2007
Description	Author affiliation: Czech Tech. Univ. in Prague, Prague (Trnka, P.)
Abstract	Integrating prior information into subspace identification methods improves their usability for industrial data, where experimental data by them self are in many cases not good enough to give a proper model. The identification experiments in the industrial environment are limited by the economical and safety reasons. However, in practical applications, there is often strong prior information about the identified system, which can be exploited in the identification. The presented algorithm formulates subspace identification as a multi-step predictor optimization. Reformulation to the Bayesian framework allows to incorporate prior information. The paper is completed with the application to the experimental data from the oil burning steam boiler with the rated power of 100 MW.
Starting Page	1161
Ending Page	1166
File Size	888928
Page Count	6
File Format	PDF
ISBN	9781424404421
ISSN	10851992
DOI	10.1109/CCA.2007.4389392
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-01
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	State-space methods MIMO Covariance matrix Usability Industrial economics Economic forecasting Environmental economics Safety Bayesian methods Technological innovation
Content Type	Text
Resource Type	Article

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