An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process

An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process

In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model...

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Main Authors: Chao Tan, Rongxin Xu, Zhongbin Wang, Lei Si, Xinhua Liu
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Computational Intelligence and Neuroscience
Online Access:http://dx.doi.org/10.1155/2016/3973627
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spelling doaj-915a8c779dcb4a21bbe027cf890ade432020-11-25T01:00:19ZengHindawi LimitedComputational Intelligence and Neuroscience1687-52651687-52732016-01-01201610.1155/2016/39736273973627An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting ProcessChao Tan0Rongxin Xu1Zhongbin Wang2Lei Si3Xinhua Liu4School of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, ChinaIn order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model is built. Then, the framework of proposed approach is built. Moreover, the constituents of GA such as tangent function roulette wheel selection (Tan-RWS) selection, uniform crossover, and nonuniform mutation are employed to enhance the performance of GFLC. Finally, two simulation examples and an industrial application example are carried out and the results indicate that the proposed method is feasible and efficient.http://dx.doi.org/10.1155/2016/3973627
collection DOAJ
language English
format Article
sources DOAJ
author Chao Tan
Rongxin Xu
Zhongbin Wang
Lei Si
Xinhua Liu
spellingShingle Chao Tan
Rongxin Xu
Zhongbin Wang
Lei Si
Xinhua Liu
An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process
Computational Intelligence and Neuroscience
author_facet Chao Tan
Rongxin Xu
Zhongbin Wang
Lei Si
Xinhua Liu
author_sort Chao Tan
title An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process
title_short An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process
title_full An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process
title_fullStr An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process
title_full_unstemmed An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process
title_sort improved genetic fuzzy logic control method to reduce the enlargement of coal floor deformation in shearer memory cutting process
publisher Hindawi Limited
series Computational Intelligence and Neuroscience
issn 1687-5265
1687-5273
publishDate 2016-01-01
description In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model is built. Then, the framework of proposed approach is built. Moreover, the constituents of GA such as tangent function roulette wheel selection (Tan-RWS) selection, uniform crossover, and nonuniform mutation are employed to enhance the performance of GFLC. Finally, two simulation examples and an industrial application example are carried out and the results indicate that the proposed method is feasible and efficient.
url http://dx.doi.org/10.1155/2016/3973627
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