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Comparison of Global Nonlinear Models and "Model-on-Demand" Estimation Applied to Identification of a RTP Wafer Reactor
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Arizona State University, AZ, USA.
Arizona State University, AZ, USA.
Honeywell Technology Center, MN, USA.
1999 (English)In: Preceedings of the 38th IEEE Conference on Decision and Control, 1999, 3950-3955 vol.4 p.Conference paper, Published paper (Refereed)
Abstract [en]

"Model on Demand" (MoD) simulation of the temperature dynamics in a simulated Rapid Thermal Process-ing (RTP) reactor is compared against various types of global models (ARX, semiphysical, combined semiphysical with neural net). The identication data is generated from a m-level pseudo-random sequence input whose parameters are specied systematically using a priori information readily available to the engineer. The MoD estimator outperforms the ARX model and two semi-physical models, while matching the performance of a combined semi-physical with neural net model. This makes MoD estimation an appealing alternative to global methods because of its reduced engineering eort and simplified a priori knowledge regarding model structure.

Place, publisher, year, edition, pages
1999. 3950-3955 vol.4 p.
Keyword [en]
Identification, Non-parametric estimation
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-91182DOI: 10.1109/CDC.1999.827976ISBN: 0-7803-5250-5 (print)OAI: oai:DiVA.org:liu-91182DiVA: diva2:617265
Conference
38th IEEE Conference on Decision and Control, Phoenix, AZ, USA, December, 1999
Available from: 2013-04-22 Created: 2013-04-17 Last updated: 2013-04-22

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  • nn-NB
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Output format
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  • asciidoc
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