SYNTHESIS OF AN ADAPTIVE FUZZY LOGIC REGULATOR FOR TEMPERATURE CONTROL IN A CHAMBER DRYER

Authors

  • N. Yevsina
  • A. Zuev
  • A. Gapon
  • M. Denysenko
  • M. Tarasenko

DOI:

https://doi.org/10.26906/SUNZ.2022.4.032

Keywords:

capillary-porous materials, fuzzy control, adaptive fuzzy logic controller, mathematical model, membership function, defuzzification

Abstract

The method of statistics is the synthesis of a fuzzy logical temperature controller for drying capillary-porous materials, which allows you to win a standard form for describing linguistic changes and the minimum set of key rules. It is indicated that the simplicity of the PID controller, as expressed through the three parameters of the adjustment and the understanding of the physical protection of the skin, at the same time, it increases the number of tasks, which can be effectively changed. For folding thermal objects, it is necessary to complete the structure of the regulator more thoroughly. It is recommended to win over vague management with insufficient knowledge of how the object of management is, but even the obviousness of managing it. The fuzzy controller is based on the vibration control, which controls, in the range of changing the dynamic pardon of the regulation and similarly to threshold values. Synthesizing a fuzzy logical controller allows the system of automatic regulation of the building to adjust the temperature of the dryer at a given level for the presence of major disturbances, as well as accurately handle the technological process of drying capillary-porous materials with a wide range of changes.

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References

Chopra S., Mitra R., Kumar V. Analysis of Fuzzy PI and PD Type Controllers Using Subtractive Clustering. International journal of computational cognition, 2006. 4(2): p. 30-34.

Ang K.H., Chong G., Li Y. PID control system analysis, design, and technology //IEEE Transactions on Control Systems Technology. 2005. Vol. 13. No. 4. P. 5599-576.

Bounemeur A., Chemachema M., Essounbouli N. New approach of robust Direct Adaptive Control of a class of SISO Nonlinear Systems, in 15th international conference on Sciences and Techniques of Automatic control & computer engineering - STA'2014,. 2014: Hammamet, Tunisia. p.725-730.

Filasov´a A., Hladk´y V., Krokavec D. Nonlinear System H∞ Fuzzy Control within Takagi-Sugeno Framework, in International Conference on Process Control (PC) June 18–21, 2013, Štrbské Pleso, Slovakia. 2013. p. 13-18.

Harpreet Singh, Madan M. Gupta, Thomas Meitzler, et al., ―Real-Life Applications of Fuzzy Logic, Advances in Fuzzy Systems, vol. 2013, Article ID 581879, 3 pages, 2013. https://doi.org/10.1155/2013/581879

Aceves-Lopes A. A simplified version of Mamdani's fuzzy controller: the natural logi controller. IEEE Transactions on fuzzy systems, 2006. 14(1): p. 16-30. DOI: 10.1109/TFUZZ.2005.861603

Ion Iancu (2012). A Mamdani Type Fuzzy Logic Controller, Fuzzy Logic - Controls, Concepts, Theories and Applications, Prof. Elmer Dadios (Ed.), ISBN: 978-953-51-0396-7.

Ковриго Ю.М. Fuzzy-регулятор для керування інерційними технологічними параметрами котлоагрегату ТЕС / Ю.М. Ковриго, О.С.Бунке, П.В. Новіков / Nauka i Studia NR 8 (169) 2017 – с. 76-84.

Fuzzy Logic Toolbox. User's Guide, Version 2.1 The MathWorks, Inc., 2001.

Published

2022-11-29

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