DocumentCode :
323354
Title :
Fuzzy control technique based on genetic algorithms optimizing and its application
Author :
Jikai, Yi ; Yan Hongping ; Hongtao, Sun ; Yuanbin, Hou
Author_Institution :
Dept. of Autom., Beijing Polytech. Univ., China
Volume :
1
fYear :
1997
fDate :
28-31 Oct 1997
Firstpage :
329
Abstract :
Aimed at a type of complex industrial production process with nonlinear dynamic properties, the Fuzzy Neural Network controller based on Genetic Algorithms was designed. The coding optimization method for the parameters of the stimulating functions of the network´s hidden nodes is the concatenated, multi parameter, mapped, and fixed point coding method. Based on this method, we can get the optimized fuzzy controller online. The step response curve of practical oven temperature control is given. The experimental results show that optimization via the Fuzzy Neural Network controller based on Genetic Algorithms is robust and effective and will find wide industrial application scope
Keywords :
fuzzy control; fuzzy neural nets; fuzzy set theory; genetic algorithms; neurocontrollers; process control; production control; temperature control; Fuzzy Neural Network controller; coding optimization method; complex industrial production process; fixed point coding method; fuzzy control technique; genetic algorithms; hidden nodes; industrial application; nonlinear dynamic properties; optimized fuzzy controller; oven temperature control; step response curve; stimulating functions; Algorithm design and analysis; Concatenated codes; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Industrial control; Optimization methods; Ovens; Production; Temperature control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
Type :
conf
DOI :
10.1109/ICIPS.1997.672793
Filename :
672793
Link To Document :
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