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Development of Fuzzy Logic Controller Based Temperature Control for KILN Control.
Subject area: Science,Engineering and Technology · Area of research: Engineering
Abstract
This research work is basically on Cement Kiln Temperature based on Fuzzy Logic Controller action. It is aimed at controlling temperature in a cement kiln using Fuzzy Logic Controller (FLC) and to analyze the system control using Matlab. The Fuzzy Logic Controller which is in three-stage processes, such as; i. Fuzzification is the process input data received by the fuzzy controller are translated into fuzzy sets, it. ii. Defuzzification which reconverts the fuzzy sets back to a crisp data which the output devices can understand and iii. Inference system (the Google machine) where the gathering and analyses of data and drawing of conclusions take place, About 90-99% of industrial controllers are using Proportional integral and Derivative (PID) controller which produce substandard cement/clinker as a result of its non-linarites. (Over burning/under burning). For this, fuzzy logic controller was used in this work, via a method of heat transfer system, to replace the conventional classical PID controller to produce quality cement/clinker. Unlike the PID, which produced overshoot and undershoot in its controllability, the FLC has zero overshoot and undershoot, since accurate production parameters are available for control. This leads to easy control and also, the production time, cost of production will be drastically reduced compared to when PID controller is being used to run the system.
Keywords
Fuzzy Logic; Fuzzification; Defuzzification; Inference System; Overshoot; Undershhot.
References
[1] Aizawa, T. (1992), Control Strategy for Automation in Onoda's Cement Plants. Onoda Cement Co. Ltd., Proe IEEE Cement Industry Technical Conference, 253-267, Japan.
[2] Algreer, M.M.F &Kuraz, Y.RM (2008); Design Fuzzy Sel: Tuning of PID Controller for Chopper-Fed DC Motor Drive, Al-Rafidain Engineering, 16(2), 54-66, 2008.
[3] Devedzic. H. (1995), Knowledge-Based Control of Rotary Kiln, Proc IEEE/IAS Int. Conf. on Industrial Automation and Control: Emerging Technologies, 452-458, Taipei.
[4] Hellendoorn, H. (1993), Design and development of fuzzy systems at siemens R&D. In Proceedings of Second IEEE International Conference on Fuzzy Systems, San Fransisco (Ca), U.S.A.
[5] Jing. Z. Tiaosheng. T., Fengesi, L &Changsi, 1 (1997), Rotary Kiin Intelligent ControlBased on Flame Image Processing. Proc IEEE Int. Conf. on Intelligent Processing. Systems, 1.792-796, Chini.
[6] Mamdani. E.H. &Assilian, S. (1975). An experiment in linguistic synthesis logic controller. International Journal of Man-Machine Studies, 7:1-13.
[7] Noshirvani, R. (2005), Rotary Cement Kiln Identification, MSc Thesis (in Persian), K N ToosiUniv of Tech, Tehran, Iran.
[8] Wang, LX (1904), Adaptive Fuzzy Systems and Control, Englewed Chiffs NJ, USA: Prentice Hall
[9] Zadeh, L.A (1973). Outline of a new approach to the analysis of complex system and decision processes. IEEE Transactions on Systems. Man and Cybernetics, 1, 28 44.
How to cite this paper
@article{1703655,
author = {Joseph, E.A, Olabode, O.R},
title = {Development of Fuzzy Logic Controller Based Temperature Control for KILN Control.},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {6},
number = {1},
pages = {684-688},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1703655.pdf},
abstract = {This research work is basically on Cement Kiln Temperature based on Fuzzy Logic Controller action. It is aimed at controlling temperature in a cement kiln using Fuzzy Logic Controller (FLC) and to analyze the system control using Matlab. The Fuzzy Logic Controller which is in three-stage processes, such as; i. Fuzzification is the process input data received by the fuzzy controller are translated into fuzzy sets, it. ii. Defuzzification which reconverts the fuzzy sets back to a crisp data which the output devices can understand and iii. Inference system (the Google machine) where the gathering and analyses of data and drawing of conclusions take place, About 90-99% of industrial controllers are using Proportional integral and Derivative (PID) controller which produce substandard cement/clinker as a result of its non-linarites. (Over burning/under burning). For this, fuzzy logic controller was used in this work, via a method of heat transfer system, to replace the conventional classical PID controller to produce quality cement/clinker. Unlike the PID, which produced overshoot and undershoot in its controllability, the FLC has zero overshoot and undershoot, since accurate production parameters are available for control. This leads to easy control and also, the production time, cost of production will be drastically reduced compared to when PID controller is being used to run the system.},
keywords = {Fuzzy Logic; Fuzzification; Defuzzification; Inference System; Overshoot; Undershhot.},
month = {July},
}