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2018 | OriginalPaper | Buchkapitel

Mathematical Model and Parametrical Identification of Ecopyrogenesis Plant Based on Soft Computing Techniques

verfasst von : Yuriy P. Kondratenko, Oleksiy V. Kozlov, Galyna V. Kondratenko, Igor P. Atamanyuk

Erschienen in: Complex Systems: Solutions and Challenges in Economics, Management and Engineering

Verlag: Springer International Publishing

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Abstract

This paper presents the development of the mathematical model and system of parametrical identification for the ecopyrogenesis (EPG) plant as a complex multi-coordinate control object on the basis of soft computing techniques. The synthesis procedure of the main parts of the EPG plant’s mathematical model, including its fuzzy parametrical identification system, adaptive-network-based fuzzy inference system for calculating of multiloop circulatory system (MCS) temperature and Mamdani type fuzzy inference system for calculating of reactor load level, is presented. The analysis of computer simulation results in the form of static and dynamic characteristics graphs of the EPG plant confirms the high adequacy of the developed complex neuro-fuzzy model to the real processes. The developed mathematical model with parametrical identification based on neuro-fuzzy technologies gives the opportunity to investigate the behavior of the given complex control object in steady and transient modes, in particular, to synthesize and adjust the intelligent controllers of the multi-coordinate automatic control system of the EPG plant.

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Vorheriges Kapitel Production Systems Optimization Using Hierarchical Planning

Nächstes Kapitel Fuzzy Data Processing Beyond Min t-Norm

Markina, L.M.: Development of new energy-saving and environmental safety technology at the organic waste disposal by ecopyrogenesis. J. Collected Works NUS 4, 8 (2011). (in Ukrainian)

Kondratenko, Y.P., Kozlov, O.V.: Computerized Monitoring and Control System for Ecopyrogenesis Technological Complex. Tribuna Plural: La revista cientifica 1, Barcelona: Reial Academia de Doctors, pp. 223–255 (2014)

Fiss, D., Wagenknecht, M., Hampel, R.: Modeling a Boiling Process Under Uncertainties. 19th Zittau Fuzzy Colloquium, Proceedings of East-West Fuzzy Colloquium 2012, Zittau, Hochschule Zittau/Goerlitz, Germany, pp. 141–146 (2012)

Han, Z.X., Yan, C.H., Zhang, Z.: Study on robust control system of boiler steam temperature and analysis on its stability. J. Zhongguo Dianji Gongcheng Xuebao Proc. Chinese Soc. Elect. Eng. 30(8), 101–109 (2010)

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)CrossRefMATH

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. Int. J. Refract. Indust. Ceramics 47(5), 283–287 (2006)

Štemberk, P., Lanska, N.: Heating System for Curing Concrete Specimens under Prescribed Temperature. In: 13th Zittau Fuzzy Collquium, Proceedings of East-West Fuzzy Colloquium 2006, Zittau, Hochschule Zittau/Goerlitz, Germany, pp. 82–88 (2006)

Skrjanc, I.: Design of fuzzy model-based predictive control for a continuous stirred-tank reactor. 12th Zittau Fuzzy Colloquium, Proceedings of East-West Fuzzy Colloquium 2005, Zittau, Hochschule Zittau/Goerlitz, Germany, pp. 126–139 (2005)

Himmelblau, D.: Applied Nonlinear Programming. Translated from English. a. ed. by of Bihovckiy, M.L., Mir, M. 534 (1974) (in Russian)

10.

Atamanyuk, I.P., Kondratenko, V.Y., Kozlov, O.V., Kondratenko, Y.P.: The Algorithm of optimal polynomial extrapolation of random processes. In: Modeling and Simulation in Engineering, Economics and Management. Engemann, K.J., Gil-Lafuente, A.M., Merigo, J L. (Eds.), International Conference MS 2012, New Rochelle, NY, USA, Proceedings. Lecture Notes in Business Information Processing 115, Springer, pp. 78–87 (2012)

11.

Drozd, J., Drozd, A.: Models, methods and means as resources for solving challenges in co-design and testing of computer systems and their components. In: Proceedings of 9th International Conference on Digital Technologies 2013, Zhilina, Slovak Republic, pp. 225–230 (2013)

12.

Tkachenko, A.N., Brovinskaya, N.M., Kondratenko, Y.P.: Evolutionary adaptation of control processes in robots operating in non-stationary environments. J. Mech. Mach. Theor. Printed in Great Britain, 18 (4), 275–278 (1983)

13.

Gerdt, V.P., Prokopenya, A.N.: Simulation of quantum error correction with Mathematica. In: Computer Algebra in Scientific Computing/ CASC’2013, Gerdt, V.P., Koepf, W., Mayr, E.W., Vorozhtsov, E. V. (Eds.), Lecture Notes in Computer Science 8136, Springer-Verlag, Berlin, pp. 116—129 (2013)

14.

Drozd, J., Drozd, A., Zashcholkin, K., Antonyuk, V., Kuznetsov, N., Kalinichenko, V., A: Concept of computing based on resources development analysis. In: Proceedings of IEEE East-West Design & Test Symposium, Rostov-on-Don, Russia, pp. 102–107 (2013)

15.

Palagin, A.V., Opanasenko, V.N.: Reconfigurable-computing technology. Cybernet. Syst. Anal. 43(5), 675–686 (2007)MathSciNetCrossRefMATH

16.

Trunov, A.N.: An adequacy criterion in evaluating the effectiveness of a model design process. East. Eur. J. Enterprise Technol. 1, 4 (73), 36–41 (2015)

17.

Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)CrossRefMATH

18.

Gil-Aluja, J.: Investment in Uncertainty. Kluwer Academic Publishers, Dordrecht, Boston, London (1999)CrossRefMATH

19.

Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst. Man Cybernet. 15 (1) (1985)

20.

Zimmermann, H.-J.: Fuzzy Set Theory—and Its Applications. Kluwer Academic Publishers, Boston/Dordrecht/London (1992)

21.

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 2, M. Jamshidi (ed.), Prentice Hall, Englewood Cliffs, NJ (1993)

22.

Zadeh, L.A.: The role of fuzzy logic in modeling, identification and control. Model. Identific. Control 15(3), 191–203 (1994)MathSciNetCrossRefMATH

23.

Yager, R.R., Filev, D.P.: Essentials of Fuzzy Modeling and Control. Wiley, New York, NY (1994)

24.

Hampel, R., Wagenknecht, M., Chaker, N.: Fuzzy Control: Theory and Practice. Physika-Verlag, Heidelberg, New York (2000)CrossRefMATH

25.

Piegat, A.: Fuzzy Modeling and Control. Physica-Verlag, Heidelberg, New York (2001)CrossRefMATH

26.

Yager, R.R., Filev, D. P.: Unified structure and parameter identification of fuzzy models. Syst. Man Cybernet. 23 (4) (1993)

27.

Lodwick, W.A., Kacprzhyk, J. (Eds): Fuzzy Optimization. Studies in Fuzziness and Soft Computing 254, Springer-Verlag, Berlin, Heidelberg (2010)

28.

Kondratenko, Y.P., Kondratenko, N.Y.: Reduced library of the soft computing analytic models for arithmetic perations with fuzzy numbers. In: Soft Computing: Developments, Methods and Applications, Alan Case (Ed), Series: Computer Science, technology and applications, NOVA Science Publishers, Hauppauge, New York, pp. 1–38 (2016)

29.

Kondratenko, Y., Kondratenko, V.: Soft computing algorithm for arithmetic multiplication of fuzzy sets based on universal analytic models. In: Information and Communication Technologies in Education, Research, and Industrial Application. Communications in Computer and Information Science 469, Ermolayev, V. et al. (Eds.): ICTERI’2014, Springer International Publishing Switzerland, pp. 49–77 (2014)

30.

Simon, D.: Training fuzzy systems with the extended Kalman filter. Fuzzy Sets Syst. 132, 189–199 (2002)MathSciNetCrossRefMATH

31.

Gil-Aluja, J., Gil-Lafuente, A.M., Klimova, A.: The optimization of the economic segmentation by means of fuzzy algorithms. J. Comput. Optim. Econom. Finance 1(3), 169–186 (2011)

32.

Shebanin, V., Atamanyuk, I., Kondratenko, Y., Volosyuk Y.: Application of fuzzy predicates and quantifiers by matrix presentation in informational resources modeling. Perspective Technologies and Methods in MEMS Design: Proceedings of the International Conference MEMSTECH-2016 Lviv-Poljana, Ukraine, pp. 146–149 (2016)

33.

Kondratenko, Y.P., Klymenko, L.P., Al Zu’bi, E.Y.M.: Structural optimization of fuzzy systems’ rules base and aggregation models. Kybernetes 42(5), 831–843 (2013)CrossRef

34.

Kondratenko, Y.P., Altameem, T.A., Al Zubi, E.Y.M.: The optimisation of digital controllers for fuzzy systems design. Advanc. Model. Anal. AMSE Period. A 47(1–2), 19–29 (2010)

35.

Kondratenko, Y.P., Al Zubi, E.Y.M.: The optimisation approach for increasing efficiency of digital fuzzy controllers. Annals of DAAAM for 2009 & Proceeding of the 20th International DAAAM Symposium. Intelligent Manufacturing and Automation, Published by DAAAM International, Vienna, Austria, pp. 1589–1591 (2009)

36.

Kondratenko, Y.P.: Robotics, automation and information systems: future perspectives and correlation with culture, sport and life science. In book: Decision Making and Knowledge Decision Support Systems. Lecture Notes in Economics and Mathematical Systems 675, Gil-Lafuente, A.M., Zopounidis, C. (Eds), Springer International Publishing Switzerland, pp. 43–56 (2015)

37.

Kauffman, A., Gil-Aluja, J.: Introduction of fuzzy sets theory to management of enterprises. Minsk, Higher School (1992). (in Russian)

38.

Gil-Aluja, J.: Elements for a theory of decision in uncertainty. Springer Science & Business Media vol. 32 (1999)

39.

Gil-Aluja, J.: Fuzzy sets in the management of uncertainty. Springer Science & Business Media vol. 145 (2004)

40.

Gil-Aluja, J.: The interactive management of human resources in uncertainty. Springer Science & Business Media vol. 11 (2013)

41.

Merigo, J.M., Gil-Lafuente, A.M., Gil-Aluja, J.: Decision making with the induced generalized adequacy coefficient. Appl. Comput. Math. 2(2), 321–339 (2011)MathSciNetMATH

42.

Gil-Aluja, J.: Handbook of management under uncertainty. Springer Science & Business Media vol. 55 (2013)

43.

Gil-Aluja, J., Gil-Lafuente, A.M., Klimova, A.: The optimization of the economic segmentation by means of fuzzy algorithms. J. Comput. Optim. Econom. Finance 1 (3), Nova Science Publishers, 169–186 (2008)

44.

Werners, B., Kondratenko, Y.P.: Tanker routing problem with fuzzy demands of served ships. Int. J. Syst. Res. Informat. Technol. 1, 47–64 (2009)

45.

Kondratenko, Y.P., Sidenko, Ie. V.: Decision-making based on fuzzy estimation of quality level for cargo delivery. In book: Recent Developments and New Directions in Soft Computing. Studies in Fuzziness and Soft Computing 317, Zadeh, L.A. et al. (Eds), Springer International Publishing Switzerland, pp. 331–344 (2014)

46.

Kondratenko, G.V., Kondratenko, Y.P., Romanov, D.O.: Fuzzy Models for Capacitive Vehicle Routing Problem in Uncertainty. In: Proceedings of 17th International DAAAM Symposium Intelligent Manufacturing and Automation: Focus on Mechatronics & Robotics, Vienna, Austria, pp. 205–206 (2006)

47.

Werners, B., Kondratenko, Y.P.: Fuzzy multi-criteria optimization for vehicle routing with capacity constraints and uncertain demands. In: Proceedings of the International Congress on Cost Control, Publ. by ACCID/ASEPUC, Barcelona, Spain, pp. 145–159 (2011)

48.

Kondratenko, Y.P., Encheva, S.B., Sidenko, E.V.: Synthesis of intelligent decision support systems for transport logistic. In: Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications 2, IDAACS’2011, Prague, Czech Republic, pp. 642–646 (2011)

49.

Gil-Lafuente, A.M.: Fuzzy Logic in Financial Analysis. Studies in Fuzziness and Soft Computing vol. 175, Springer, Berlin (2005)

50.

Merigó, J.M., Gil-Lafuente, A.M., Gil-Aluja, J.: A new aggregation method for strategic decision making and its application in assignment theory. Afr. J. Bus. Manag. 5(11), 4033–4043 (2011)MATH

51.

Gil-Aluja, J., Gil-Lafuente, A.M., Merigó, J.M.: Using homogeneous groupings in portfolio management. Expert Syst. Appl. 38(9), 10950–10958 (2011)CrossRef

52.

Butenko, S., Gil-Lafuente, J., Pardalos, P.M. (eds.): Optimal Strategies in Sports Economics and Management. Springer-Vertag, Heidelberg, Dordrecht, London, New York (2010)

53.

Gil Aluja, J. (ed.): Les Universitats En El Centenari Del Futbol Club Barcelona. Estudis En L’Ambit De L’Esport, Proleg, Josef Lluis Nunez (1999)

54.

Gil-Lafuente, A.M., Merigo, J.M.: Decision making techniques in political management. In book: Fuzzy Optimization. In: Studies in Fuzziness and Soft Computing vol. 254, Lodwick, W.A., Kacprzhyk, J. (Eds), Springer, Berlin, Heidelberg, pp. 389–405 (2010)

55.

Kacprzyk, J., Yager, R.R., Zadrożny, S.: A fuzzy logic based approach to linguistic summaries of databases. Int. J. Appl. Math. Comput. Sci. 10(4), 813–834 (2000)MATH

56.

Oh, S.K., Pedrycz, W.: The design of hybrid fuzzy controllers based on genetic algorithms and estimation techniques. J. Kybernetes 31(6), 909–917 (2002)CrossRef

57.

Suna, Q., Li, R., Zhang, P.: Stable and optimal adaptive fuzzy control of complex systems using fuzzy dynamic model. J. Fuzzy Sets Syst. 133, 1–17 (2003)MathSciNetCrossRef

58.

Vachkov, G., Kiyota, Y., Komatsu, K.: Identification of dynamic cause-effect relations for systems performance evaluation. Appl. Sci. Soft Comput. Advan. Soft Comput. 24, 187–194 (2004)

59.

Hayajneh, M.T., Radaideh, S.M., Smadi, I.A.: Fuzzy logic controller for overhead cranes. Eng. Comput. 23(1), 84–98 (2006)CrossRefMATH

60.

Wang, L., Kazmierski, T.J.: VHDL-AMS based genetic optimization of fuzzy logic controllers. Int. J. Comput. Math. Elect. Electron. Eng. 26(2), 447–460 (2007)CrossRefMATH

61.

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. Indust. Manag. Data Syst. 108(7), 947–972 (2008)CrossRef

62.

Kondratenko, Y.P., Kozlov, O. V.: Fuzzy Controllers in Reactors Control Systems of Multiloop Pyrolysis Plants. 19th Zittau Fuzzy Colloquium, Proceedings of East-West Fuzzy Colloquium 2012, Zittau, Hochschule Zittau/Goerlitz, Germany, 15–22 (2012)

63.

Rotach, V. Y.: Automatic Control Theory of Heat and Power Processes: M, Energoatomizdat, 296 (1985). (in Russian)

64.

Kondratenko, Y. P., Kozlov, O. V.: Mathematical Model of Ecopyrogenesis Reactor with Fuzzy Parametrical Identification. In: Recent Developments and New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing 342. Lotfi A. Zadeh et al. (Eds.). Berlin, Heidelberg: Springer, pp. 439–451 (2016)

65.

Kondratenko, Y. P., Kozlov, O. V.: Mathematic Modeling of Reactor’s Temperature Mode of Multiloop Pyrolysis Plant. Lecture Notes in Business Information Processing: Modeling and Simulation in Engineering, Economics and Management 115, K. J. Engemann, A. M. Gil-Lafuente, J. M. Merigo (Eds.), Berlin, Heidelberg: Springer, pp. 178–187 (2012)

66.

Kondratenko, Y. P., Kozlov, O. V., Klymenko, L. P., Kondratenko, G.V.: Synthesis and Research of Neuro-Fuzzy Model of Ecopyrogenesis Multi-circuit Circulatory System. Advance Trends in Soft Computing, Studies in Fuzziness and Soft Computing 312, Berlin, Heidelberg: Springer, pp. 1–14 (2014)

67.

Jang, J.-S.R.: ANFIS: Adaptive-Network-based Fuzzy Inference Systems. IEEE Transactions on Systems, Man, and Cybernetics 23(3), 665–685 (1993)CrossRef

68.

Jang, J.-S. R., Sun, C.-T., Mizutani, E.: Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. Prentice Hall (1996)

69.

Dimirovski, G. M., Lokevenc, I. I., Tanevska, D. J.: Applied Adaptive Fuzzy-neural Inference Models: Complexity and Integrity Problems. Intelligent Systems, Proceedings of 2nd International IEEE Conference 1 (22–24), 45–52 (2004)

70.

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, T. Kwater, B. Twarog (Eds.), Monographs in Applied Informatics, Wydawnictwo Uniwersytety Rzeszowskiego, Rzeszow, Poland, 97–120 (2013)

Titel: Mathematical Model and Parametrical Identification of Ecopyrogenesis Plant Based on Soft Computing Techniques
verfasst von: Yuriy P. Kondratenko
Oleksiy V. Kozlov
Galyna V. Kondratenko
Igor P. Atamanyuk
Verlag: Springer International Publishing
Buch: Complex Systems: Solutions and Challenges in Economics, Management and Engineering
Print ISBN: 978-3-319-69988-2

Electronic ISBN: 978-3-319-69989-9

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-69989-9_13

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