An Interval Type-2 Fuzzy Controller Based on Data-Driven Parameters Extraction for Cement Calciner Process

The stable control of the calciner plant is vital for the clinker quality and energy consumption in the cement calcination process. However, traditional calciner control strategies cannot efficiently deal with complicated characteristics, such as the changes in the material component, process distur...

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Bibliographic Details
Published inIEEE access Vol. 8; pp. 61775 - 61789
Main Authors Zheng, Jinquan, Du, Wenli, Nascu, Ioana, Zhu, Yuanming, Zhong, Weimin
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Calcination
Calciner process control
Clinker
Clustering
Coal
Controllers
Cyclones
Disturbances
Energy consumption
Fuzzy control
Fuzzy logic
interval type-2 fuzzy C-means cluster
interval type-2 fuzzy controller
Kilns
Process control
Strategy
Temperature control
Uncertainty
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Summary:The stable control of the calciner plant is vital for the clinker quality and energy consumption in the cement calcination process. However, traditional calciner control strategies cannot efficiently deal with complicated characteristics, such as the changes in the material component, process disturbances and uncertainty, and meanwhile cannot obtain knowledge from data. For these challenges, an intelligent control strategy based on an interval type-2 fuzzy logic controller (IT2FLC) is proposed by making full use of process data in this work. The feedback IT2FLC combines with feedforward IT2FLC, taking into account various disturbances. An improved interval type-2 fuzzy C-means (IT2FCM) clustering algorithm is used to extract membership functions and rules, taking into account process uncertainty. Finally, the proposed control strategy is applied to control a calciner simulation process with practical data. The results show that the proposed strategy has better performance than the type-1 fuzzy logic controller (T1FLC) and can better meet the demand for real-life applications.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2983476