Skip to main content

Synthesis and Optimization of Green Fuzzy Controllers for the Reactors of the Specialized Pyrolysis Plants

  • Chapter
  • First Online:
Green IT Engineering: Social, Business and Industrial Applications

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 171))

Abstract

This paper presents the developed by the authors generalized step-by-step method of synthesis and optimization of green fuzzy controllers (FC) for the automatic control systems (ACS) of the reactor’s temperature of the specialized pyrolysis plants (SPP). The proposed method gives the opportunity to synthesize and optimize Mamdani type green FCs of the temperature modes of the SPPs reactors that provide (a) high accuracy and quality indicators of temperature control, (b) low energy consumption in the process of functioning as well as (c) relatively simple software and hardware implementation. The initial synthesis of the structure and parameters of green FCs is implemented on the basis of expert assessments and recommendations. Their further optimization for improving the quality indicators, reducing energy consumption and simplification of soft/hardware realization is carried out using specific optimization procedures by means of mathematical programming methods. In order to study and validate the effectiveness of the developed method the design of the Mamdani type green FC for the temperature ACS of the pyrolysis reactor of the experimental SPP has been carried out in this work. The developed green FC has a relatively simple hardware and software implementation as well as allows to achieve high quality indicators of temperature modes control at a sufficiently low energy consumption, that confirms the high efficiency of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ryzhkov, S.S., Markina, L.M.: Experimental researches of organic waste recycling method of multiloop circulating pyrolysis. J. Collected Works NUS 5, 100–106 (2007). (in Russian)

    Google Scholar 

  2. 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)

    Google Scholar 

  3. Kondratenko, Y.P., Korobko, O.V., Kozlov, O.V.: PLC-based systems for data acquisition and supervisory control of environment-friendly energy-saving technologies. In: Kharchenko, V., Kondratenko, Y., Kacprzyk J. (eds.) Green IT Engineering: Concepts, Models, Complex Systems Architectures, Studies in Systems, Decision and Control, vol. 74, pp. 247–267. Springer International Publishing, Berlin, Heidelberg (2017). https://doi.org/10.1007/978-3-319-44162-7_13

    Google Scholar 

  4. Kondratenko, Y.P., Kozlov, O.V.: Mathematic modeling of reactor’s temperature mode of multiloop pyrolysis plant. In: Modeling and Simulation in Engineering, Economics and Management. Lecture Notes in Business Information Processing, vol. 115, pp. 178–187 (2012). https://doi.org/10.1007/978-3-642-30433-0_18

    Google Scholar 

  5. Kondratenko, Y.P., Kozlov, O.V., Kondratenko, G.V., Atamanyuk, I.P.: Mathematical model and parametrical identification of ecopyrogenesis plant based on soft computing techniques. In: Berger-Vachon, C., Lafuente, A.M.G., Kacprzyk, J., Kondratenko, Y., Merigó, J.M., Morabito, C.F. (eds.) Complex Systems: Solutions and Challenges in Economics, Management and Engineering. Studies in Systems, Decision and Control, vol. 125, pp. 201–233. Springer International Publishing, Berlin, Heidelberg (2018). https://doi.org/10.1007/978-3-319-69989-9_13

    Google Scholar 

  6. Kondratenko, Y.P., Kozlov, O.V.: Mathematical model of ecopyrogenesis reactor with fuzzy parametrical identification. In: Zadeh, L.A., et al. (eds.) Recent Developments and New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol. 342, pp. 439–451. Springer-Verlag, Berlin, Heidelberg (2016). https://doi.org/10.1007/978-3-319-32229-2_30

    Google Scholar 

  7. Kharchenko, V., et al. (eds.).: Green IT engineering: concepts, models, complex systems architectures. In: Decision and Control, vol. 74. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-44162-7

    Google Scholar 

  8. Kharchenko, V., et al. (eds.).: Green IT engineering: components, networks and systems implementation. In: Studies in Systems, Decision and Control, vol. 105. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-55595-9

    Google Scholar 

  9. Drozd, J., Drozd, A., Antoshchuk, S.: Green IT engineering in the view of resource-based approach. In: Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (eds.) Green IT Engineering: Concepts, Models, Complex Systems Architectures, Studies in Systems, Decision and Control, vol. 74, pp. 43–65. Springer International Publishing, Berlin, Heidelberg (2017). https://doi.org/10.1007/978-3-319-44162-7_3

    Google Scholar 

  10. Palagin, A.V., Opanasenko, V.N.: Design and application of the PLD-based reconfigurable devices. In: Adamski, M., Barkalov, A., Wegrzyn, M. (eds.) Design of Digital Systems and Devices. Lecture Notes in Electrical Engineering, vol. 79, pp. 59–91. Verlag, Springer, Berlin, Heidelberg (2011)

    Chapter  Google Scholar 

  11. Kharchenko, V., Illiashenko, O.: Concepts of green IT engineering: taxonomy, principles and implementation. In: Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (eds.) Green IT Engineering: Concepts, Models, Complex Systems Architectures. Studies in Systems, Decision and Control, vol. 74, pp. 3–19. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-44162-7_1

    Google Scholar 

  12. Kuchuk, G., Kovalenko, A., Kharchenko, V., Shamraev, A.: Resource-oriented approaches to implementation of traffic control technologies in safety-critical I&C systems. In: Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (eds.) Green IT Engineering: Components, Networks and Systems Implementation, Studies in Systems, Decision and Control, vol. 105, pp. 313–337. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-55595-9_15

    Chapter  Google Scholar 

  13. Kondratenko, Y., Gordienko, E.: Implementation of the neural networks for adaptive control system on FPGA. In: Katalinic, B. (ed.) Annals of DAAAM for 2012, Proceeding of the 23th International DAAAM Symposium on “Intelligent Manufacturing and Automation”, vol. 23, no. 1, pp. 0389–0392. DAAAM International, Vienna, Austria, EU (2012)

    Google Scholar 

  14. Zadeh, L.A., Abbasov, A.M., Yager, R.R., Shahbazova, S.N., Reformat, M.Z. (eds.): Recent Developments and New Directions in Soft Computing. In: STUDFUZ, vol. 317. Springer, Cham (2014)

    MATH  Google Scholar 

  15. Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds.): Advance Trends in Soft Computing. Springer-Verlag, Cham (2013)

    Google Scholar 

  16. 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)

    Google Scholar 

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

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  19. Piegat, A.: Fuzzy Modeling and Control, vol. 69. Physica (2013)

    Google Scholar 

  20. He, X., He, S.: Research of energy consumption pattern classification based on fuzzy logic and RBF networks in hydraulic systems. Sens. Transducers 205(10), 58–62 (2016)

    Google Scholar 

  21. 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)

    Article  Google Scholar 

  22. Kondratenko, Y., Gerasin, O., Topalov, A.: A simulation model for robot’s slip displacement sensors. Int. J. Comput. 15(4), 224–236 (2016). Retrieved from http://computingonline.net/computing/article/view/854

  23. Pasieka, M., Grzesik, N., Kuźma, K.: Simulation modeling of fuzzy logic controller for aircraft engines. Int. J. Comput. 16(1), 27–33 (2017). Retrieved from http://computingonline.net/computing/article/view/868

  24. Gomolka, Z., Dudek-Dyduch, E., Kondratenko, Y.P.: From homogeneous network to neural nets with fractional derivative mechanism. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) Artificial Intelligence and Soft Computing. Lecture Notes in Artificial Intelligence 10245, 16th International Conference ICAISC 2017, Zakopane, Poland, 11–15 June 2017. Proceedings, Part 1, pp. 52–63. Springer International Publishing, Cham (2017). https://doi.org/10.1007/978-3-319-59063-9_5

    Google Scholar 

  25. Tanaka, K., Wang, H.O.: Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach. Wiley, New York, USA (2001)

    Book  Google Scholar 

  26. Hampel, R., Wagenknecht, M., Chaker N.: Fuzzy Control: Theory and Practice, p. 410. Physika-Verlag, Heidelberg, New York (2000)

    Google Scholar 

  27. Kondratenko, Y.P., Kozlov, O.V., Kondratenko, G.V., Atamanyuk, I.P.: Mathematical model and parametrical identification of ecopyrogenesis plant based on soft computing techniques. In: Berger-Vachon, C. et al. (eds.) Complex Systems: Solutions and Challenges in Economics, Management and Engineering, Studies in Systems, Decision and Control, vol. 125, pp. 201–233. Springer, Berlin, Heidelberg (2018). https://doi.org/10.1007/978-3-319-69989-9_13

    Google Scholar 

  28. Driankov, D., Hellendoorn, H., Reinfrank, M.: An Introduction to Fuzzy Control. Springer Science & Business Media (2013)

    Google Scholar 

  29. Merigo, J.M., Gil-Lafuente, A.M., Yager, R.R.: An overview of fuzzy research with bibliometric indicators. Appl. Soft Comput. 27, 420–433 (2015)

    Article  Google Scholar 

  30. Rotshtein, A.P., Rakytyanska, H.B.: Fuzzy Evidence in Identification, Forecasting and Diagnosis, vol. 275. Springer, Heidelberg (2012)

    Book  Google Scholar 

  31. Von Altrock, C.: Applying fuzzy logic to business and finance. Optimus 2, 38–39 (2002)

    Google Scholar 

  32. 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)

    Article  MathSciNet  Google Scholar 

  33. 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)

    Article  Google Scholar 

  34. Lodwick, W.A., Kacprzhyk, J. (eds.).: Fuzzy optimization. In: STUDFUZ, vol. 254. Springer-Verlag, Berlin, Heidelberg (2010)

    Google Scholar 

  35. Kondratenko, Y.P., Simon, D.: Structural and parametric optimization of fuzzy control and decision making systems. In: Zadeh, L. et al. (eds.) Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol. 361, pp. 273–289 (2018). Springer, Cham. https://doi.org/10.1007/978-3-319-75408-6_22

    Chapter  Google Scholar 

  36. Jayaram, B.: Rule reduction for efficient inferencing in similarity based reasoning. Int. J. Approximate Reasoning 48(1), 156–173 (2008)

    Article  MathSciNet  Google Scholar 

  37. Yam, Y., Baranyi, P., Yang, C.-T.: Reduction of fuzzy rule base via singular value decomposition. IEEE Trans. Fuzzy Syst. 7(2), 120–132 (1999)

    Article  Google Scholar 

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

    Google Scholar 

  39. Simon, D.: H∞ estimation for fuzzy membership function optimization. Int. J. Approximate Reasoning 40, 224–242 (2005)

    Article  MathSciNet  Google Scholar 

  40. Simon, D.: Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence. Wiley (2013)

    Google Scholar 

  41. 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). http://dx.doi.org/10.1108/K-03-2013-0053

    Article  Google Scholar 

  42. Simon, D.: Design and rule base reduction of a fuzzy filter for the estimation of motor currents. Int. J. Approximate Reasoning 25, 145–167 (2000)

    Article  Google Scholar 

  43. Ishibuchi, H., Yamamoto, T.: Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining. Fuzzy Sets Syst. 141(1), 59–88 (2004)

    Article  Google Scholar 

  44. Koczy, L.T., Hirota, K.: Size reduction by interpolation in fuzzy rule bases. IEEE Trans. Syst. Man Cybern. B Cybern. 27(1), 14–25 (1997)

    Article  Google Scholar 

  45. Alcalá, R., Alcalá-Fdez, J., Gacto, M.J., Herrera, F.: Rule base reduction and genetic tuning of fuzzy systems based on the linguistic 3-tuples representation. Soft. Comput. 11(5), 401–419 (2007)

    Article  Google Scholar 

  46. Pedrycz, W., Li, K., Reformat, M.: Evolutionary reduction of fuzzy rule-based models. In: Fifty Years of Fuzzy Logic and Its Applications, STUDFUZ, vol. 326, pp. 459–481. Springer, Cham (2015)

    Chapter  Google Scholar 

  47. Simon, D.: Sum normal optimization of fuzzy membership functions. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10, 363–384 (2002)

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  49. Kondratenko, Y., Korobko, V., Korobko, O., Kondratenko, G., Kozlov, O.: Green-IT approach to design and optimization of thermoacoustic waste heat utilization plant based on soft computing. In: Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (eds.) Green IT Engineering: Components, Networks and Systems Implementation. Studies in Systems, Decision and Control, vol. 105, pp. 287–311. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-55595-9_14

    Chapter  Google Scholar 

  50. Kondratenko, Y.P., Kozlov, O.V., Korobko, O.V., Topalov, A.M.: Synthesis and optimization of fuzzy control system for floating Dock’s docking operations. In: Santos, W. (ed.) Fuzzy Control Systems: Design, Analysis and Performance Evaluation, pp. 141–215. Nova Science Publishers, Hauppauge, NY (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuriy Kondratenko .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kozlov, O., Kondratenko, G., Gomolka, Z., Kondratenko, Y. (2019). Synthesis and Optimization of Green Fuzzy Controllers for the Reactors of the Specialized Pyrolysis Plants. In: Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (eds) Green IT Engineering: Social, Business and Industrial Applications. Studies in Systems, Decision and Control, vol 171. Springer, Cham. https://doi.org/10.1007/978-3-030-00253-4_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00253-4_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00252-7

  • Online ISBN: 978-3-030-00253-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics