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
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