Abstract
This paper presents the development of the neuro-fuzzy mathematical model of the ecopyrogenesis (EPG) complex multiloop circulatory system (MCS). The synthesis procedure of the neuro-fuzzy model, including its adaptive-network-based fuzzy inference system for temperature calculating (ANFISTC) training particularities with input variables membership functions of different types is presented. The analysis of computer simulation results in the form of static and dynamic characteristics graphs of the MCS as a temperature control object confirms the high adequacy of the developed model to the real processes. The developed neuro-fuzzy mathematical model gives the opportunity to investigate the behavior of the temperature control object in steady and transient modes, in particular, to synthesize and adjust the temperature controller of the MCS temperature automatic control system (ACS).
Keywords
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References
Markina, L.M.: Development of New Energy-saving and Environmental Safety Technology at the Organic Waste Disposal by Ecopyrogenesis. J. Collected Works of NUS 4, 8 (2011) (in Ukrainian)
Chaikin, B.S., Mar’yanchik, G.E., Panov, E.M., Shaposhnikov, P.T., Vladimirov, V.A., Volovik, I.S., Makarevich, B.A.: State-of-the-art Plants for Drying and High-Temperature Heating of Ladles. International Journal of Refractories and Industrial Ce-ramics 47(5), 283–287 (2006)
Štemberk, P., Lanska, N.: Heating System for Curing Concrete Specimens under Pre-scribed Temperature, 13th Zittau Fuzzy Collqui-um. In: Proceedings of East-West Fuzzy Col-loquium 2006, Zittau, Hochschule Zittau/Goerlitz, Germany, pp. 82–88 (2006)
Han, Z.X., Yan, C.H., Zhang, Z.: Study on Robust Control System of Boiler Steam Temperature and Analysis on its Stability. Journal of Zhongguo Dianji Gongcheng Xuebao, Proceedings of the Chinese Society of Electrical Engineering 30(8), 101–109 (2010)
Fiss, D., Wagenknecht, M., Hampel, R.: Modeling a Boiling Process Under Uncertain-ties. In: 19th Zittau Fuzzy Colloquium, Proceedings of East-West Fuzzy Colloquium 2012, Zittau, Hochschule Zittau/Goerlitz, Germany, pp. 141–122 (2012)
Skrjanc, I.: Design of Fuzzy Model-Based Predictive Control for a Continuous Stirred-Tank Reactor. In: 12th Zittau Fuzzy Colloquium. In: Proceedings of East-West Fuzzy Colloquium 2005, Zittau, Hochschule Zittau/Goerlitz, Germany, pp. 126–139 (2005)
Xiao, Z., Guo, J., Zeng, H., Zhou, P., Wang, S.: Application of Fuzzy Neural Network Controller in Hydropower Generator Unit. J. Kybernetes 38(10), 1709–1717 (2009)
Kondratenko, Y.P., Kozlov, O.V.: Fuzzy Controllers in Reactors Control Systems of Multiloop Pyrolysis Plants. In: 19th Zittau Fuzzy Colloquium. In: Proceedings of East-West Fuzzy Colloquium 2012, Zittau, Hochschule Zittau/Goerlitz, Germany, pp. 15–22 (2012)
Zadeh, L.A.: Fuzzy sets, Information and Control, vol. 8, pp. 338–353 (1965)
Jamshidi, M., Vadiee, N., Ross, T.J. (eds.): Fuzzy Logic and Control: Software and Hardware Application. Prentice Hall Series on Environmental and Intelligent Manufacturing Systems (M. Jamshidi, ed.), vol. 2. Prentice Hall, Englewood Cliffs (1993)
Jamshidi, M.: On Software and Hardware Application of Fuzzy Logic. In: Yager, R.R., Zadeh, L.A. (eds.) Fuzzy Sets, Neural Networks and Soft Computing, vol. 20, Van Nostrand Reinhold, NY (1994)
Hampel, R., Wagenknecht, M., Chaker, N.: Fuzzy Control: Theory and Practice. Physika-Verlag. Heidelberg (2000)
Piegat, A.: Fuzzy Modeling and Control. Physica-Verlag, Heidelberg (2001)
Oh, S.K., Pedrycz, W.: The Design of Hybrid Fuzzy Controllers Based on Genetic Al-gorithms and Estimation Techniques. J. Kybernetes 31(6), 909–917 (2002)
Suna, Q., Li, R., Zhang, P.: Stable and Optimal Adaptive Fuzzy Control of Complex Systems Using Fuzzy Dynamic Model. J. Fuzzy Sets and Systems 133, 1–17 (2003)
Hayajneh, M.T., Radaideh, S.M., Smadi, I.A.: Fuzzy logic controller for overhead cranes. Engineering Computations 23(1), 84–98 (2006)
Wang, L., Kazmierski, T.J.: VHDL-AMS Based Genetic Optimisation of Fuzzy Logic Controllers. International Journal for Computation and Mathematics in Electrical and Electronic Engineering 26(2), 447–460 (2007)
Ho, G.T.S., Lau, H.C.W., Chung, S.H., Fung, R.Y.K., Chan, T.M., Lee, C.K.M.: Fuzzy rule sets for enhancing performance in a supply chain network. Industrial Management & Data Systems 108(7), 947–972 (2008)
Kondratenko, Y.P., Kozlov, O.V., Atamanyuk, I.P., Korobko, O.V.: Computerized Control System for the Pyrolysis Reactor Load Level Based on the Neural Network Controllers. Computing in Science and Technology (2012/2013); Kwater, T., Twarog, B. (eds.): Monographs in Applied Informatics, pp. 97–120. Wydawnictwo Uniwersytety Rzeszowskiego, Rzes-zow (2013)
Jang, J.-S.R.: ANFIS: Adaptive-Network-based Fuzzy Inference Systems. IEEE Transactions on Systems, Man, and Cybernetics 23(3), 665–685 (1993)
Jang, J.-S.R., Sun, C.-T., Mizutani, E.: Neuro-Fuzzy and Soft Computing: A Computa-tional Approach to Learning and Machine Intelligence. Prentice Hall (1996)
Dimirovski, G.M., Lokevenc, I.I., Tanevska, D.J.: Applied Adaptive Fuzzy-neural Infe-rence Models: Complexity and Integrity Problems. In: Proceedings of 2nd International IEEE Conference Intelligent Systems, vol. 1, 22-24, pp. 45–52 (2004)
Rotach, V.Y.: Automatic Control Theory of Heat and Power Processes, M, Energoatomizdat, p. 296 (1985) (in Russian)
Kondratenko, Y.P., Kozlov, O.V.: Mathematic modeling of reactor’s temperature mode of multiloop pyrolysis plant. In: Engemann, K.J., Gil-Lafuente, A.M., Merigó, J.M. (eds.) MS 2012. LNBIP, vol. 115, pp. 178–187. Springer, Heidelberg (2012)
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Kondratenko, Y.P., Kozlov, O.V., Klymenko, L.P., Kondratenko, G.V. (2014). Synthesis and Research of Neuro-Fuzzy Model of Ecopyrogenesis Multi-circuit Circulatory System. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds) Advance Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-03674-8_1
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DOI: https://doi.org/10.1007/978-3-319-03674-8_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03673-1
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