Adaptive Control of Meniscus Velocity in Continuous Caster based on NARX Neural Network Model

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Adaptive Control of Meniscus Velocity in Continuous Caster based on NARX Neural Network Model

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Adaptive Control of Meniscus Velocity in Continuous Caster based on NARX Neural Network Model

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

IFAC-PapersOnLine (13th IFAC Workshop on Adaptive and Learning Control Systems ALCOS 2019)

ISBN

—

ISSN

24058963

e-ISSN

—

Počet stran výsledku

6

Strana od-do

222-227

Název nakladatele

Elsevier

Místo vydání

Amsterdam

Místo konání akce

Winchester

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000507495600038