Title :
Research on optimizing fuzzy controllers based on genetic algorithm
Author :
Kaijun Xu ; Chunyan Zhang ; Shuwang Wang ; Hannian Zhang
Author_Institution :
Sch. of Electr. & Inf., Nanjing Coll. of Inf. Technol., Nanjing, China
Abstract :
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.
Keywords :
control system synthesis; fuzzy control; genetic algorithms; nonlinear functions; adequate datum; fuzzy controller design; fuzzy controller optimization; fuzzy rule models; input variable; input-output data; membership function parameter; nonlinear function; real coded genetic algorithm; Accuracy; Approximation algorithms; Approximation methods; Biological cells; Fuzzy systems; Genetic algorithms; Input variables;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
DOI :
10.1109/ICACI.2012.6463223
