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Published in: Metallurgist 1-2/2022

01-07-2022

Adaptive Control of Process Units at JSC OEMK Named after A. A. Ugarov Based on Neural Network for Tuning Controller Parameters

Authors: K. A. Chernov, A. V. Fomin, A. I. Glushchenko

Published in: Metallurgist | Issue 1-2/2022

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Abstract

The development and implementation of adaptive control systems, which are used to tune the parameters of PI-controllers of the metal pre-heating furnace for rolling and the water-air cooling circuit of continuous-casting machine of JSC OEMK im. A. A. Ugarov, are considered. The current adaptive control system based on open-loop control is analyzed, its disadvantages are shown. The proposed method of PI-controller automatic tuning to keep the transient quality using a neural tuner is described for both of the above mentioned plants. The use of the developed adaptive system makes it possible to improve the quality of control and minimize the number of situations when the controlled value exceeds the technological range.
Literature
1.
go back to reference Z. G. Salikhov, G. G. Arunyants, and A. L. Rutkovsky, Optimal Control Systems of Complex Industrial Objects [In Russian], Moscow, Teploénergetik (2004). Z. G. Salikhov, G. G. Arunyants, and A. L. Rutkovsky, Optimal Control Systems of Complex Industrial Objects [In Russian], Moscow, Teploénergetik (2004).
2.
go back to reference A. G. Alexandrov and I. G. Rezkov, “Implementation of frequency adaptive control for SIEMENS controller,” in: Conference Proceedings of XI All-Russian Workshop for Young Scientists “Upravlenie Bol’shimi Sistemami” [in Russian], IPU RAS, Moscow (2014), pp. 1156–1166. A. G. Alexandrov and I. G. Rezkov, “Implementation of frequency adaptive control for SIEMENS controller,” in: Conference Proceedings of XI All-Russian Workshop for Young Scientists “Upravlenie Bol’shimi Sistemami” [in Russian], IPU RAS, Moscow (2014), pp. 1156–1166.
3.
go back to reference B. A. Staroverov, V. V. Olonichev, and M. A. Smirnov, “Implementation of adaptive control systems for process units having linux-controllers,” Promyshlennye ASU i Kontrollery, No. 7, 48–53 (2012). B. A. Staroverov, V. V. Olonichev, and M. A. Smirnov, “Implementation of adaptive control systems for process units having linux-controllers,” Promyshlennye ASU i Kontrollery, No. 7, 48–53 (2012).
4.
go back to reference M. V. Lankin, “Software implementation of the adaptive control algorithm with demagnetizing field,” in: Conference Proceedings “Teoriya, Metody i Sredstva Izmereniy, Kontrolya, i Diagnostiki” [in Russian], NPO TEMP, Novocherkassk (2002), pp. 26–31. M. V. Lankin, “Software implementation of the adaptive control algorithm with demagnetizing field,” in: Conference Proceedings “Teoriya, Metody i Sredstva Izmereniy, Kontrolya, i Diagnostiki” [in Russian], NPO TEMP, Novocherkassk (2002), pp. 26–31.
5.
go back to reference V. Ya. Rotach, “Adaptation in process control systems,” Promyshlennye ASU i Kontrollery, No. 1, 4–10 (2005). V. Ya. Rotach, “Adaptation in process control systems,” Promyshlennye ASU i Kontrollery, No. 1, 4–10 (2005).
6.
go back to reference B.-M. Pfeiffer, “Towards “plug and control”: self-tuning temperature controller for PLC,” Int. J. of Adaptive Control and Signal Processing, No. 14. 519–532 (2000). CrossRef B.-M. Pfeiffer, “Towards “plug and control”: self-tuning temperature controller for PLC,” Int. J. of Adaptive Control and Signal Processing, No. 14. 519–532 (2000). CrossRef
7.
go back to reference D. V. Belyshev and V. I. Gurman, “Software package for multimethod intelligent algorithms for optimal control,” Avtomatika i Telemekhanika, No. 6, 60–67 (2003). D. V. Belyshev and V. I. Gurman, “Software package for multimethod intelligent algorithms for optimal control,” Avtomatika i Telemekhanika, No. 6, 60–67 (2003).
8.
go back to reference D. Ch. Chuong, “Software implementation of a fuzzy PID controller on an industrial cross controller,” Promyshlennye ASU i Kontrollery, No. 3, 36–38 (2008). D. Ch. Chuong, “Software implementation of a fuzzy PID controller on an industrial cross controller,” Promyshlennye ASU i Kontrollery, No. 3, 36–38 (2008).
9.
go back to reference M. V. Burakov and A. P. Kirpichnikov, “Synthesis of discrete neuro-pid controller,” Promyshlennye ASU i Kontrollery, No. 2, 22–29 (2006). M. V. Burakov and A. P. Kirpichnikov, “Synthesis of discrete neuro-pid controller,” Promyshlennye ASU i Kontrollery, No. 2, 22–29 (2006).
10.
go back to reference Yu. I. Eremenko, D. A. Poleshchenko, and A. I. Glushchenko, “Using a neural network optimizer for pi-controller parameters to control heating furnaces in various operating modes,” Upravlenie Bol’shimi Sistemami, No. 56, 143–175 (2015). Yu. I. Eremenko, D. A. Poleshchenko, and A. I. Glushchenko, “Using a neural network optimizer for pi-controller parameters to control heating furnaces in various operating modes,” Upravlenie Bol’shimi Sistemami, No. 56, 143–175 (2015).
11.
go back to reference A. G. Aleksandrov, M. V. Palenov, and I. G. Rezkov, “Adaptive PID controller-CHAR-PID-1,” Avtomatizatsiya v Promyshlennosti, No. 9, 58–61 (2011). A. G. Aleksandrov, M. V. Palenov, and I. G. Rezkov, “Adaptive PID controller-CHAR-PID-1,” Avtomatizatsiya v Promyshlennosti, No. 9, 58–61 (2011).
12.
go back to reference R. Vilanova and A. Visioli, PID Control in the Third Millennium. Lessons Learned and New Approaches, London, Springer (2012). CrossRef R. Vilanova and A. Visioli, PID Control in the Third Millennium. Lessons Learned and New Approaches, London, Springer (2012). CrossRef
13.
go back to reference L. P. Myshlyaev, E. I. L’vova, K. A. Ivushkin, and D. A. Ageev, “Synthesis and study of identification algorithms based on closed dynamic systems,” in: System Identification and Control Problems [in Russian], Sicpro’15, IPURAS, Moscow (2015), pp. 397–418. L. P. Myshlyaev, E. I. L’vova, K. A. Ivushkin, and D. A. Ageev, “Synthesis and study of identification algorithms based on closed dynamic systems,” in: System Identification and Control Problems [in Russian], Sicpro’15, IPURAS, Moscow (2015), pp. 397–418.
14.
go back to reference A. V. Fomin and A. I. Glushchenko, “Improving control quality of heating furnaces at JSC “OEMK” by using open-loop pi controllers,” Metallurg, No. 3, 37–42 (2019). A. V. Fomin and A. I. Glushchenko, “Improving control quality of heating furnaces at JSC “OEMK” by using open-loop pi controllers,” Metallurg, No. 3, 37–42 (2019).
15.
go back to reference A. I. Glushchenko, “Method for determining the learning rate of a neural network for online adjustment of linear controllers in controlling nonlinear objects,” Upravlenie Bol’shimi Sistemami, No. 72, 52–107 (2018). A. I. Glushchenko, “Method for determining the learning rate of a neural network for online adjustment of linear controllers in controlling nonlinear objects,” Upravlenie Bol’shimi Sistemami, No. 72, 52–107 (2018).
Metadata
Title
Adaptive Control of Process Units at JSC OEMK Named after A. A. Ugarov Based on Neural Network for Tuning Controller Parameters
Authors
K. A. Chernov
A. V. Fomin
A. I. Glushchenko
Publication date
01-07-2022
Publisher
Springer US
Published in
Metallurgist / Issue 1-2/2022
Print ISSN: 0026-0894
Electronic ISSN: 1573-8892
DOI
https://doi.org/10.1007/s11015-022-01302-5

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