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Zastosowanie Modelu Sterowania Predykcyjnego w energooszczędnej technologii prostego pieca tlenowego
Języki publikacji
Abstrakty
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.
Spełnienie warunku jednoczesnego osiągnięcia pożądanego składu chemicznego i temperatury metalu jest zapewnione poprzez kontrolę zużycia tlenu i położenia palnika tlenowego. Zaprezentowano metodę rozwiązania Modelu Sterowania Predykcyjnego z funkcjonalnością kwadratową w obecności ograniczeń. Wdrożenie opisanego rozwiązania przyczyni się do zwiększenia udziału złomu i skrócenia czasu topnienia bez zmiany procesu technologicznego.
Rocznik
Tom
Strony
70--74
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
- National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Department of Automation of heat-and-power engineering processes, Kyiv, Ukraine
autor
- National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Department of Automation of heat-and-power engineering processes, Kyiv, Ukraine
Bibliografia
- [1] 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 [http://doi.org/10.1016/j.ifacol.2019.11.355].
- [2] Bogushevskiy V.S., et al.: System for the BOF Process Control. The Advanced Science Open Access Journal 5/2013, 23–27.
- [3] Bogushevskiy V.S., Zuboka C.M.: Mathematical modeling of the converter process by energy-saving technology. Technological complexes 2/2013, 32–38.
- [4] Camacho E.F., Bordons A.: Model Predictive Control. 2nd ed, Springer-Verlag London 2007.
- [5] Cherneha D.F., et al.: Fundamentals of metallurgical production of metals and alloys. High School, Kyiv 2006.
- [6] Ghosh S., et al.: BOF process dynamics. Mineral Processing and Extractive Metallurgy 128(1)/2018, 1–17 [http://doi.org/10.1080/25726641.2018.1544331].
- [7] Kouvaritakis B., Cannon M.: Model Predictive Control Classical, Robust and Stochastic. Springer-Verlag, London 2016.
- [8] 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 [http://doi.org/10.1016/j.ifacol.2017.08.2065].
- [9] 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 [http://doi.org/10.15587/1729-4061.2018.132229].
- [10] 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 [http://doi.org/10.1155/2015/483674].
- [11] MathWorks. Design Controller Using MPC Designer. http://www.mathworks.com/help/mpc/gs/introduction.html?ue (available 5.09. 2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-95aa107f-d3c2-4909-9a15-b1d9c5efc34d