Adaptive Control of Meniscus Velocity in Continuous Caster based on NARX Neural Network Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F19%3A00007327" target="_blank" >RIV/46747885:24220/19:00007327 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.ifacol.2019.12.653" target="_blank" >https://doi.org/10.1016/j.ifacol.2019.12.653</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ifacol.2019.12.653" target="_blank" >10.1016/j.ifacol.2019.12.653</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive Control of Meniscus Velocity in Continuous Caster based on NARX Neural Network Model
Original language description
Meniscus velocity in continuous casting is critical in determining the quality of the steel. Due to the complex nature of the various interacting phenomena in the process, designing model-based controllers can prove to be a challenge. In this paper a NARX neural network model is trained to describe the complex relationship between the applied current to an Electromagnetic Brake (EMBr) and the measured meniscus velocity. The data for the model is obtained using a laboratory scale continuous casting plant. Adaptive Model Predictive Control (MPC) was used to deal with the non-linearity of the model by adapting the prediction model to the different operating conditions. The controller uses the EMBr as an actuator to keep the meniscus velocity within the optimum range, and reject disturbances that occur during the casting process such as changing the casting speed.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IFAC-PapersOnLine (13th IFAC Workshop on Adaptive and Learning Control Systems ALCOS 2019)
ISBN
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ISSN
24058963
e-ISSN
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Number of pages
6
Pages from-to
222-227
Publisher name
Elsevier
Place of publication
Amsterdam
Event location
Winchester
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000507495600038