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Computational Intelligence and Neuroscience
Volume 2016, Article ID 3973627, 14 pages
http://dx.doi.org/10.1155/2016/3973627
Research Article

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

1School of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, China
2Xuyi Mine Equipment and Materials R&D Center, China University of Mining & Technology, Huai’an, China
3School of Information and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China

Received 4 August 2015; Revised 30 December 2015; Accepted 18 January 2016

Academic Editor: Marc Van Hulle

Copyright © 2016 Chao Tan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.