MODEL PREDICTIVE CONTROL APPLICATION IN THE ENERGY SAVING TECHNOLOGY OF BASIC OXYGEN FURNACE
Article Sidebar
Open full text
Issue Vol. 10 No. 2 (2020)
-
TRANSISTOR-BASED TEMPERATURE MEASURING DEVICE
Oleksandra Hotra4-7
-
ANALYSIS OF ALL-PASS FILTERS APPLICATION TO ELIMINATE NEGATIVE EFFECTS OF LOUDNESS WAR TREND
Marcin Maciejewski, Wojciech Surtel, Krzysztof Nowak8-11
-
LOGICAL CLASSIFICATION TREES IN RECOGNITION PROBLEMS
Igor Povhan12-15
-
RANKING OF WEBSITES CREATED WITH THE USE OF ISOWQ RANK ALGORITHM
Mariusz Duka16-19
-
OVERVIEW OF BROADBAND INFORMATION SYSTEMS ARCHITECTURE FOR CRISIS MANAGEMENT
Jacek Wilk-Jakubowski20-23
-
TIME-VARIANT MODEL OF HEAT-AND-MASS EXCHANGE FOR STEAM HUMIDIFIER
Igor Golinko, Volodymyr Drevetskiy24-27
-
NONSTATIONARY HEAT CONDUCTION IN MULTILAYER GLAZING SUBJECTED TO DISTRIBUTED HEAT SOURCES
Natalia Smetankina, Oleksii Postnyi28-31
-
REAL-TIME MONITORING OF CELL CULTURES WITH NICKEL COMB CAPACITORS
Andrzej Kociubiński, Dawid Zarzeczny, Maciej Szypulski, Aleksandra Wilczyńska, Dominika Pigoń, Teresa Małecka-Massalska, Monika Prendecka32-35
-
AN OVERVIEW OF CLASSIFICATION METHODS FROM DERMOSCOPY IMAGES IN SKIN LESION DIAGNOSTIC
Magdalena Michalska, Oksana Boyko36-39
-
SOFTWARE DEVELOPMENT FOR SMART HOME PROCESS CONTROL
Vitalii Kopeliuk, Vira Voronytska, Volodymyr Havryliuk40-43
-
EXERGY-BASED CONTROL STRATEGY IN A DWELLING VENTILATION SYSTEM WITH HEAT RECOVERY
Volodymyr Voloshchuk, Mariya Polishchuk44-47
-
ANALYSIS OF THE ELECTRICITY METERING SYSTEM FOR OWN ELECTRIC SUBSTATION NEEDS
Sergiy Stets, Andriy Stets48-51
-
RESEARCH ON THE COMBUSTION PROCESS USING TIME SERIES
Żaklin Grądz52-55
-
RESEARCH AND SIMULATION OF THE LOCAL NAVIGATION SYSTEM OF TERRESTRIAL MOBILE ROBOT
Andrii Rudyk, Viktoriia Rudyk, Mykhailo Matei56-61
-
DESIGN OF MULTIFUNCTION SIMULATOR FOR ENGINE ROOM PERSONNEL TRAINING
Artem Ivanov, Igor Kolosov, Vadim Danyk, Sergey Voronenko, Yurii Lebedenko, Hanna Rudakova62-69
-
MODEL PREDICTIVE CONTROL APPLICATION IN THE ENERGY SAVING TECHNOLOGY OF BASIC OXYGEN FURNACE
Oleksandr Stepanets, Yurii Mariiash70-74
Archives
-
Vol. 12 No. 4
2022-12-30 16
-
Vol. 12 No. 3
2022-09-30 15
-
Vol. 12 No. 2
2022-06-30 16
-
Vol. 12 No. 1
2022-03-31 9
-
Vol. 11 No. 4
2021-12-20 15
-
Vol. 11 No. 3
2021-09-30 10
-
Vol. 11 No. 2
2021-06-30 11
-
Vol. 11 No. 1
2021-03-31 14
-
Vol. 10 No. 4
2020-12-20 16
-
Vol. 10 No. 3
2020-09-30 22
-
Vol. 10 No. 2
2020-06-30 16
-
Vol. 10 No. 1
2020-03-30 19
-
Vol. 9 No. 4
2019-12-16 20
-
Vol. 9 No. 3
2019-09-26 20
-
Vol. 9 No. 2
2019-06-21 16
-
Vol. 9 No. 1
2019-03-03 13
-
Vol. 8 No. 4
2018-12-16 16
-
Vol. 8 No. 3
2018-09-25 16
-
Vol. 8 No. 2
2018-05-30 18
-
Vol. 8 No. 1
2018-02-28 18
Main Article Content
DOI
Authors
Abstract
The fulfilment of the condition for the simultaneous achievement of the desired chemical composition and temperature of the metal is ensured by controlling the oxygen consumption and the position of the oxygen impeller lance. The method for solving Model Predictive Control with quadratic functionality in the presence of constraints is given. Implementation of the described solutions will contribute to increasing the proportion of scrap and reducing the melting period without changing of technological process.
Keywords:
References
Backman J., et al.: Methods and Tools of Improving Steel Manufacturing Processes: Current State and Future Methods. International Federation of Automatic Control PapersOnLine 52(13)/2019, 1174–1179. DOI: https://doi.org/10.1016/j.ifacol.2019.11.355
Bogushevskiy V.S., et al.: System for the BOF Process Control. The Advanced Science Open Access Journal 5/2013, 23–27.
Bogushevskiy V.S., Zuboka C.M.: Mathematical modeling of the converter process by energy-saving technology. Technological complexes 2/2013, 32–38.
Camacho E.F., Bordons A.: Model Predictive Control. 2nd ed, Springer-Verlag London 2007. DOI: https://doi.org/10.1007/978-0-85729-398-5
Cherneha D.F., et al.: Fundamentals of metallurgical production of metals and alloys. High School, Kyiv 2006.
Ghosh S., et al.: BOF process dynamics. Mineral Processing and Extractive Metallurgy 128(1)/2018, 1–17. DOI: https://doi.org/10.1080/25726641.2018.1544331
Kouvaritakis B., Cannon M.: Model Predictive Control Classical, Robust and Stochastic. Springer-Verlag, London 2016. DOI: https://doi.org/10.1007/978-1-4471-5058-9_7
Ruuska J., et al.: Mass-balance Based Multivariate Modelling of Basic Oxygen Furnace Used in Steel Industry. International Federation of Automatic Control PapersOnLine 50(1)/2017, 13784–13789. DOI: https://doi.org/10.1016/j.ifacol.2017.08.2065
Stepanets O., Mariiash Y.: Analysis of Influence of Technical Features of a PID – controller Implementation on The Dynamics of Automated Control System. Eastern-European Journal of Enterprise Technologies 3(2)/2018, 60–69. DOI: https://doi.org/10.15587/1729-4061.2018.132229
Zhang J.: Optimal Control Problem of Converter Steelmaking Production Process Based on Operation Optimization Method. Discrete Dynamics in Nature and Society 2015, Article ID 483674. DOI: https://doi.org/10.1155/2015/483674
MathWorks. Design Controller Using MPC Designer. https://www.mathworks.com/help/mpc/gs/introduction.html?ue (available 5.09. 2018).
Article Details
Abstract views: 427
License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
