Data-driven Modelling, Learning and Stochastic Predictive Control for the Steel Industry

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Herceg, DomagojIMT School for Advanced Studies Lucca, Italy (author)

Data-driven Modelling, Learning and Stochastic Predictive Control for the Steel Industry

Article/chapterEnglish2017

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Piscataway, NJ :Institute of Electrical and Electronics Engineers (IEEE),2017
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LIBRIS-ID:oai:DiVA.org:ltu-64960
https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-64960URI
https://doi.org/10.1109/MED.2017.7984308DOI
https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-33130URI

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Language:English
Summary in:English

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SwePubSwePub

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Subject category:ref swepub-contenttype
Subject category:kon swepub-publicationtype

Notes

Funding details: KU Leuven; Funding details: BOF/STG-15-043, KU Leuven; Funding details: University of Engineering and Technology, Peshawar; Funding details: McDonnell Center for Systems Neuroscience; Funding details: 636834, Technische Universiteit Delft; Funding details: FÃ©dÃ©ration Wallonie-Bruxelles; Funding details: LuleÃ¥ Tekniska Universitet; Funding details: Department of Electrical Engineering, Chulalongkorn University; Funding details: H2020 LEIT Advanced Manufacturing and Processing
The steel industry involves energy-intensive processessuch as combustion processes whose accurate modellingvia first principles is both challenging and unlikely to leadto accurate models let alone cast time-varying dynamics anddescribe the inevitable wear and tear. In this paper we addressthe main objective which is the reduction of energy consumptionand emissions along with the enhancement of the autonomy ofthe controlled process by online modelling and uncertaintyawarepredictive control. We propose a risk-sensitive modelselection procedure which makes use of the modern theoryof risk measures and obtain dynamical models using processdata from our experimental setting: a walking beam furnaceat Swerea MEFOS. We use a scenario-based model predictivecontroller to track given temperature references at the threeheating zones of the furnace and we train a classifier whichpredicts possible drops in the excess of Oxygen in each heatingzone below acceptable levels. This information is then used torecalibrate the controller in order to maintain a high qualityof combustion, therefore, higher thermal efficiency and loweremissions

Subject headings and genre

TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Reglerteknik hsv//swe
ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Control Engineering hsv//eng
Advanced Process Control
Machine Learning
Stochastic Model Predictive Control
Risk-sensitive Model Selection
Cyber-Physical Systems
Reglerteknik
Control Engineering

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Georgoulas, GeorgiosLuleå tekniska universitet,Signaler och system(Swepub:ltu)geogeo (author)
Sopasakis, PantelisKU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Lulea University of Technology, Sweden (author)
Castaño Arranz, MiguelLuleå tekniska universitet,Signaler och system,KU Leuven, Belgium(Swepub:ltu)migcas (author)
Patrinos, Panagiotis K.KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Lulea University of Technology, Sweden (author)
Bemporad, AlbertoIMT School for Advanced Studies Lucca, Italy (author)
Niemi, JanRISE,MEFOS AB,Swerea MEFOS, Box 812, Luleå (author)
Nikolakopoulos, GeorgeLuleå tekniska universitet,Signaler och system,KU Leuven, Belgium(Swepub:ltu)geonik (author)
Georgoulas, GeorgeKU Leuven, Belgium (author)
IMT School for Advanced Studies Lucca, ItalySignaler och system (creator_code:org_t)

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In:2017 25th Mediterranean Conference on Control and Automation, MED 2017Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), s. 1361-13669781509045334

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By the author/editor: Herceg, Domagoj; Georgoulas, Geor ...; Sopasakis, Pante ...; Castaño Arranz, ...; Patrinos, Panagi ...; Bemporad, Albert ...; show more...; Niemi, Jan; Nikolakopoulos, ...; Georgoulas, Geor ...; show less...

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ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Electrical Engin ...; and Control Engineer ...

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