Using BP Neural Network to Determine the Membership Function of the Input of Fuzzy Control System
DOI:
CSTR:
Author:
Affiliation:

Clc Number:

TP212

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    While design the fuzzy controller, it is very important to determine the membership function of fuzzy variables.The data can be broadly classified as fuzzy sets by using the classification property of the BP neural network. The author selects a BP neural network with one hide layer and uses S function to the input and hide layer, and linear function to the output layer.Advanced BP algorithm isused to train the BP neural network in the environment of MATLAB . The nearer to the target values is the better the last output is.With the trained BP network , the membership values of the inputs can be got ten. This method has high rate and low error.

    Reference
    Related
    Cited by
Get Citation

张新燕.用BP网求解模糊控制器输入量的隶属函数[J].重庆大学学报,2004,27(5):54~56

Copy
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:January 18,2004
  • Adopted:
  • Online:
  • Published:
Article QR Code