Title: Fuzzy self-learning control of glass tempering and annealing temperature based on the optimised genetic big data analysis algorithm

Authors: Xiaokan Wang; Hairong Dong; Xiuming Yao; Xubin Sun

Addresses: School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China; Mechanical and Electrical Department, Henan Mechanical and Electrical Vocational College, Zhengzhou 450002, China ' School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China ' School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China ' School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Abstract: The temperature control of glass tempering and annealing process has the problems of the time varying parameters and time lag characteristic. In order to solve this problem, this paper proposes a self-learning fuzzy controller based on improved genetic algorithm and big data analysis. The proposed algorithm can quickly search the global optimal factor by using the big data temperature. Thus the fuzzy control rules are perfected and corrected. The simulation results demonstrate that the proposed control algorithm is suitable for systems with time varying parameters and time lag characteristic.

Keywords: annealing temperature; big data analysis; fuzzy control; self learning; improved genetic algorithm.

DOI: 10.1504/IJRIS.2018.091129

International Journal of Reasoning-based Intelligent Systems, 2018 Vol.10 No.1, pp.43 - 50

Received: 21 Apr 2017
Accepted: 16 Jun 2017
Published online: 11 Apr 2018 *

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