Use of Defuzzification Methods for a Dry Cement Rotary Kiln

International Journal of Civil Engineering

© 2025 by SSRG - IJCE Journal

Volume 12 Issue 8

Year of Publication : 2025

Authors : Brayham Smit Tunco Quispe, Luciano Gabriel Cuayla Flores, German Alberto Echaiz Espinoza, Pedro Alberto Mamani Apaza, Fernando Echaiz Espinoza

10.14445/23488352/IJCE-V12I8P103

How to Cite?

Brayham Smit Tunco Quispe, Luciano Gabriel Cuayla Flores, German Alberto Echaiz Espinoza, Pedro Alberto Mamani Apaza, Fernando Echaiz Espinoza, "Use of Defuzzification Methods for a Dry Cement Rotary Kiln," SSRG International Journal of Civil Engineering, vol. 12,  no. 8, pp. 32-49, 2025. Crossref, https://doi.org/10.14445/23488352/IJCE-V12I8P103

Abstract:

Controlling nonlinear thermal systems like rotary cement kilns is a long-standing problem in industrial automation since they are dynamic and hard to predict. Fuzzy Logic Controllers (FLCs) present a strong alternative; nonetheless, the essential defuzzification phase - responsible for transforming fuzzy outputs into actionable values - has been inadequately examined in comparative analyses. This project creates a Mamdani-type FLC with 88 rules based on experts and four main inputs: combustion temperature, furnace torque, CO percentage, and preheater temperature. It will be used to control a high-capacity rotary kiln. We comprehensively examine five defuzzification methods: centroid, bisector, Smallest of Maximum (SOM), Middle of Maximum (MOM), and Largest of Maximum (LOM), using simulations generated in MATLAB’s Fuzzy Logic Toolbox. The results reveal that the output is generally consistent among approaches, except for the kiln feed rate, which is quite sensitive. The research illustrates that the selection of defuzzification strategy significantly influences control performance, with maxima-based approaches providing enhanced stability. These results provide practical advice for developing strong fuzzy controllers for complicated industrial processes.

Keywords:

Defuzzification techniques, Fuzzy Logic Controller, Mamdani inference, Nonlinear process control, Rotary kiln automation.

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