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A Study on Improved Fuzzy Neural Network Controller for Air-Condition with Frequency Change

  • Shuqing Wang
  • Zipeng Zhang
  • Zhihuai Xiao
  • Xiaohui Yuan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5552)

Abstract

The environment of room temperature is complicated and it is difficult to get precise mathematics model for the control of air-condition with frequency change. It is difficult using conventional fuzzy control way to control air-condition to get better control performance. Fuzzy neural network has strong fuzzy reasoning ability and learning ability, which can control air-condition with frequency change to get better control effect. In this paper, an improved fuzzy neural network controller is designed to control air-condition. In order to overcome the weakness of slow learning speed for fuzzy neural network, GAs is employed to optimize parameters of fuzzy neural network. In order to improve training speed and overcome the shortcoming of local optimization, the designed genetic algorithm is improved based on the control system. Simulating experiment shows that the designed controller has better controlling effect than other conventional fuzzy controller.

Keywords

Fuzzy neural network Genetic algorithm Air-condition with frequency change Room temperature Optimization control 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Shuqing Wang
    • 1
  • Zipeng Zhang
    • 1
  • Zhihuai Xiao
    • 2
  • Xiaohui Yuan
    • 3
  1. 1.Hubei University of TechnologyChina
  2. 2.Wuhan UniversityWuhanChina
  3. 3.Huazhong University of Science and TechnologyWuhanChina

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