Research on optimizing fuzzy controllers based on genetic algorithm

A novel method based on the concepts of genetic algorithm (GA) is proposed to design a fuzzy controller directly from some gathered input-output data. The proposed method can pick up fuzzy rule models and determine the parameters of membership functions of each input variable automatically from adeq...

Full description

Saved in:
Bibliographic Details
Published in2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) pp. 545 - 548
Main Authors Kaijun Xu, Chunyan Zhang, Shuwang Wang, Hannian Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
Accuracy
Approximation algorithms
Approximation methods
Biological cells
Fuzzy systems
Genetic algorithms
Input variables
Online AccessGet full text

Cover

More Information
Summary:A novel method based on the concepts of genetic algorithm (GA) is proposed to design a fuzzy controller directly from some gathered input-output data. The proposed method can pick up fuzzy rule models and determine the parameters of membership functions of each input variable automatically from adequate datum. And it can optimize parameters of membership functions using a real coded genetic algorithms. Finally, a typical nonlinear function is utilized to illustrate the effectiveness of the proposed method.
ISBN:9781467317436
1467317438
DOI:10.1109/ICACI.2012.6463223