Skip to main content

Predictive Control of Complex Industrial Thermal Processes

  • Chapter
  • First Online:
Book cover Complex Systems

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 55))

  • 1433 Accesses

Abstract

This paper is oriented toward presenting the advanced predictive control methods in thermal processes which have been developed and/or practically implemented at the ASE Institute in FEEIT Skopje. The thermal processes usually have high fuel consumption and therefore the optimization of the fuel costs is extremely important. With reducing of these costs we dramatically reduce the costs of the final product. In such direction, the advanced control methods for thermal processes usually lean toward faster response and increased robustness, in this case, using predictive techniques.

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. Dimirovski, G.M., Dourado, A., Ikonen, E., Kortela, U., Pico, J., Ribeiro, B., Stankovski, M.J., Tulunay, E.: Learning control of thermal systems. In: Astrorm, K.J., Albertos, P., Blanke, M., Isidori, A., Schaufelberger, W., Sanz, R. (eds.) Control of Complex Systems, pp. 317–337. Springer, London (2001)

    Chapter  Google Scholar 

  2. Dimirovski, G.M., Dinibutun, A.T., Vukobratovic, M., Zhao, J.: Optimizing supervision and control for industrial furnaces: predictive control based design. In: Sgurev, V., Dimirovski, G., Hadjiski, M. (eds.) Automatic Systems for Building the Infrastructure in Developing Countries—Global and Regional Aspects DECOM-04. Union for Automation & Informatics of Bulgaria and the IFAC, Sofia, BG 17–28 (2004)

    Google Scholar 

  3. Dimirovski, G.M., Angelovski, R.S., Stankovski, M.J.: Enhanced control of induction heating processes of welded tubes. In: De Carli, A. (ed.) Low Cost Automation: Techniques, Components and Instrument Applications, pp. 461–469. The IFAC and Pergamon Press, Oxford (1990)

    Google Scholar 

  4. Dimirovski, G.M., Hadzi-Nicev, N., Ivanoski, M., Gyorsoski, J.: Design and implementation of an automated industrial electrical reheating furnace. In: Goodwin, G.C., Evans, R.J., (eds.) Automatic Control—World Congress 1993, Applications II, vol. 4, 451–454. Pergamon Press, Oxford, UK (1994)

    Google Scholar 

  5. Sadaoui, N., Gough, N.E., Ting, I.H., Dimirovski, G.M.: Computer-aided study of non-linear systems using input-output approach. In: Atherton D.P., (General Chair) Proceedings of the 30th IEEE Conference on Decision and Control, Brighton, UK, vol. 3, pp. 2799–2804. The IEEE, New York, NY (1991)

    Google Scholar 

  6. Ting, I.H., Gough, N.E., Dimirovski, G.M., Deskov, V.P.: Application of the characteristic pattern methodology to the design of a reheat furnace multi-variable control system. In: Proceedings of the Institution of Mechanical Engineers Pt. I Systems & Control Engineering, 206 (I2), pp. 29–34 (1992)

    Google Scholar 

  7. Zhu, Y.C., Backx, A.C.P.M.: MIMO process identification for controller design: test signals, nominal model and error bounds. In: Identification and System Parameter Estimation 1991, Proceedings of Selected Papers from the 9th IFAC/IFORS Symposium, vol. 1, pp. 127–132. The IFAC and Pergamon Press, Oxford, UK (1992)

    Google Scholar 

  8. Stankovski, M.J., Gough, N.E., Dimirovski, G.M.: Temperature Control of Large Furnaces—A Survey. Technical report IDP290, School of Computing and Information Technology, University of Wolverhampton, Wolverhampton, UK (1992)

    Google Scholar 

  9. Rhine, J.M., Tucker, R.J.: Modeling of Gas-Fired Furnaces and Boilers. McGraw-Hill, New York (1991)

    Google Scholar 

  10. Stankovski, M.J.: Non-conventional Control of Industrial Energy Processes in Large Heating Furnaces. Ph.D. thesis; in Macedonian, SS Cyril and Methodius University, Faculty of EE, Skopje, MK (1997)

    Google Scholar 

  11. Stankovski, M.J., Dimirovski, G.M., Gough, N.E., Hanus, R.: Industrial furnace control: an experiment in iterative identification and design. In: Patton, R.J., Goodall, R., Fleming, P. (eds.) Proceedings of the UKACC International Conference on Control, IEE Publication No. 455, vol. II, pp. 946–951. The Institution of Electrical Engineers, London, UK (1998)

    Google Scholar 

  12. Stankovski, M.J., Dimirovski, G.M., Gough, N.E., Ting, I.H., Kolemishevska-Gugulovska, T.D.: Identification and digital control system design for 20 MW gas-fired pipe heating furnace. In: Dourado, A., et al. (eds.) Controlo 98 Proceedings, vol. 1, pp. 87–92. The APCA and Universidade de Coimbra, Coimbra, PT (1998)

    Google Scholar 

  13. Albertos, P.: Iterative controller design. In: Proceedings ESF-COSY’97 Workshop on Learning Control Systems, Sao Silvestre (PT). The ESF & CIS – UC, Coimbra. Paper 11, pp. 1–15 (1997)

    Google Scholar 

  14. Gevers, M.: Learning from identification and control design (Plenary Lecture). In: Albertos, P. (ed.) Proceedings Joint ESF-COSY’96 Workshop, Valencia (E): The ESF & DISCA-UPV, Valencia, ES, Theme 3, PL.3, pp. 1–60 (1996)

    Google Scholar 

  15. Keviczky, L., Banyasz, Cs.: On the dialectics of identification and control in iterative learning schemes. In: Albertos, P. (ed.) Proceedings of Joint ESF-COSY’96 Workshop, Valencia: The ESF & DISCA-UPV, Valencia ES, Theme 3, Paper 1, pp. 1–24 (1996)

    Google Scholar 

  16. Astrom, K.J.: Matching criteria for control and identification. In: Proceedings of the 2nd European Control Conference, Groningen, The Netherlands, pp. 248–251. The EUCA, Groningen, NL (1993)

    Google Scholar 

  17. Allgöwer, F., Badgwell, T., Qin, J., Rawlings, J., Wright, S.: Nonlinear predictive control and moving horizon estimation—An introductory overview. In: Frank, P.M. (ed.) Advances in Control: Highlights of ECC’99, pp. 391–449. Springer, Berlin (1999)

    Chapter  Google Scholar 

  18. Jing, Y., Dimirovski, G.M.: Decentralized stabilization control for composite systems with time delays and uncertainties. In: Solaiman, B., (ed.) Proceedings of the 3rd IEEE Conference Information and Communication Technologies, Damascus, Syria, vol. 1, pp. 1404–1409. The IEEE, Piscataway, NJ, USA (2006)

    Google Scholar 

  19. Pregelj, B., Gerkšič, S.: Multiple model approach to multi-parametric model predictive control of a nonlinear process—A simulation case study. http://as.utia.cas.cz/files/113.pdf (2006)

  20. Onnen, C., Babuska, R., Kaymak, U., Sousa, J.M., Verbruggen, H.B., Isermann, R.: Genetic algorithms for optimization in predictive control. Control Eng. Pract. 5(10), 1363–1372 (1997)

    Article  Google Scholar 

  21. Blasco, X., Martinez, M., Senent, J., Sanchis, J.: Generalized predictive control using genetic algorithms (GAGPC). An application to control of a non-linear process with model uncertainty. Eng. Appl. Artif. Intell. 11, 355–367 (1998)

    Article  Google Scholar 

  22. Potocnik, P., Grabec, I.: Model predictive control using neural networks and genetic algorithms. In: Dville, M., Owens, R. (eds.) Proceedings of the 16th IMACS World Congress 2000 on Scientific Computation, Applied Mathematics and Simulation, pp. 1–6. Brussels Paris, The IMACS (2000)

    Google Scholar 

  23. Al-Duwaish, H., Naeem, W.: Nonlinear model predictive control of Hammerstein and Wiener models using genetic algorithms. In: Control Applications 2001 (CCA ’01), Proceedings of the 2001 IEEE International Conference, the IEEE, Piscataway, NJ, USA, pp. 465–469 (2001)

    Google Scholar 

  24. Stojanovski, G.S., Stankovski, M.J.: Model predictive controller employing genetic algorithm optimization of thermal processes with non-convex constraints. In: Popa, R. (ed) Genetic Algorithms in Applications,  pp. 19–34 (2012)

    Google Scholar 

  25. Stojanovski, G.S., Stankovski, M.J., Dimirovski, G.M.: Multiple-model model predictive control for high consumption industrial furnaces. FACTA UNIVERSITATIS Ser. Autom. Control Robot. 9(1), 131–139 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Goran Stojanovski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Stojanovski, G., Stankovski, M. (2016). Predictive Control of Complex Industrial Thermal Processes. In: Dimirovski, G. (eds) Complex Systems. Studies in Systems, Decision and Control, vol 55. Springer, Cham. https://doi.org/10.1007/978-3-319-28860-4_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-28860-4_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28858-1

  • Online ISBN: 978-3-319-28860-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics