SavedAdd your journal

Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2003 / Cilt: 3 - Sayı: 1

Fuzzy control systems for thermal processes: synthesis, design and implementation

Georgi M. DIMIROVSKI
Lyupco N. ANTOVSKI
Mile J. STANKOVSKI
Tatyana D.K. GUGULOVSKA
Pages
759–773
Publication Date
2022-10-18
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Quality and performance of the overall fuzzy process control system have been investigated and validated to fulfill the required quality specifications.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:A completed case study on fuzzy logic control of thermal processes has been carried out using a professional laboratory oven for industrial purpose as an experimental test rig.
📊
Key Findings & Data:It involved system engineering design analysis, control synthesis, and implementation as well as application software and signal interface design and development.
💡
Conclusion & Impact:Quality and performance of the overall fuzzy process control system have been investigated and validated to fulfill the required quality specifications.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

A completed case study on fuzzy logic control of thermal processes has been carried out using a professional laboratory oven for industrial purpose as an experimental test rig. It involved system engineering design analysis, control synthesis, and implementation as well as application software and signal interface design and development. The resulting expertise and lessons learned are reported in this contribution. The structure of PD type of fuzzy logic controllers is closely discussed along with synthesis issues of membership functions and knowledge rule base. Special software was developed using Microsoft Visual Studio, C++ and Visual basic for GUI for a standard PC platform. The application software designed and implemented has four modules: FIS editor, Rule Editor, Membership Function Editor and Fuzzy Controller with Rule Viewer. Quality and performance of the overall fuzzy process control system have been investigated and validated to fulfill the required quality specifications.

🔖

Cite This Article

DIMIROVSKI, G. M., ANTOVSKI, L. N., STANKOVSKI, M. J., GUGULOVSKA, T. D. (2022). Fuzzy control systems for thermal processes: synthesis, design and implementation. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 3 - Sayı: 1, 759–773. https://ajindex.com/articles/543915

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (13)

  1. J. Aracil, A. Ollero, and A. Garcia-Cerezo, “Stability indeces for the global analysis of expert control systems.” IEEE Trans. Systems, Man, and Cybernetics, vol. 19, no. 5, pp. 998- 1007, 1989
  2. K. J. Astroem and B. Wittenmark, Computer-Controlled Systems (3rd ed.). Englewood Cliffs, NJ: Prentice-Hall, 1997
  3. J. A. Bernard, “Use of rule-based systems for process control.” IEEE Control Systems Mag, vol. 8, no.5, pp. 3-13, 1988
  4. J. J. Buckley, “Universal fuzzy controllers.” Automatica, vol. 28, no. 6, pp. 1245-1248, 1992
  5. A. di Nola, W. Pedrycz, S. Sessa, and P. Z. Wang, “Fuzzy relation equation under a class of triangular norms: A survey and new results.” Stochastica, vol. 8, no. 2, pp. 99-145, 1984
  6. G. M. Dimirovski, R. Hanus, V. N. Burzevski, O. L. Iliev, and S. V. Ikonomovski, “A generic fuzzy controller for multivariable processes,” in Proceedings of the 1994 IEEE Industrial Electronics Conference, G. Buja, Gen. Chair and Ed., Bologna, IT, vol. 2, pp. 1359- 1364. New York, NY: The IEEE, 1994
  7. G. M. Dimirovski, Lectures on Computer Process Control: Pt. 5 Knowledge-base Fuzzylogic Decision and Control (in Macedonian). Skopje, MK: FEE-ASE Institute, SS Cyril & Methodius University, 1995
  8. G. M. Dimirovski, A. Dourado, N. E. Gough, B. Ribeiro, M. J. Stankovski, I. H. Ting, E. Tulunay, “On learning control in industrial furnaces and boilers,” in Proceedings of the 2000 IEEE International Symposium on Intelligent Control, P. P. Grumpos, N. T. Kousulas, and M. Polycarpou, Eds., Rion Patras, GR, pp. 67-72. Piscataway NJ: The IEEE and University of Patras, 2000
  9. G. M. Dimirovski, G. M., A. Dourado, E. Ikonen, U. Kortela, J. Pico, B. Ribeiro, M. J. Stankovski, E. Tulunay, Learning Control of Thermal Systems, in K. J. Astroem, P. Albertos, M. Blanke, A. Isidori, W. Schauefelberger, and R. Sanz, Eds., Control of Complex Systems, Chapter 14, pp. 317-387. London, UK: SpringerVerlag, 2001
  10. D. Driankov, H. Hellendorn, and M. Reinfrank, An Introduction to Fuzzy Control. Heidelberg, DE: Springer-Verlag,, 1993
  11. H. Hellendorn and C. Tomas, “Defuzzification in fuzzy controllers.” J. Intelligent and Fuzzy Systems, vol. 1, no. 2, pp. 109-123, 1993
  12. H. K. Khalil, Nonlinear Systems. New York, NY: Macmillan, 1992
  13. W. J. M. Kickert and H. R. Van Nauta Lemke, “Application of fuzzy controller in a warm water plant.” Automatica, vol. 12, no. 4, pp. 301-308, 1976. J. Kiszka, M. Gupta, and P. Nikiforuk, “Energetistic stability of f