DocumentCode :
467671
Title :
Optimizing Parameters of Fuzzy Controller Based on Genetic Algorithm
Author :
Liu, Chao-ying ; Wang, Hui-fang ; Song, Xue-ling ; Song, Zhe-ying ; Li, Kai
Author_Institution :
Hebei Univ. of Sci. & Technol., Shijiazhuang
Volume :
1
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
413
Lastpage :
418
Abstract :
For effects of the parameters of fuzzy controller with nonlinear scaling factors on a system´s performance and the parameters are interactive, this paper proposes a method based on genetic algorithm (GA) to tune and optimize the parameters. Simulation results show that system which adopted the parameters derived from the method has better dynamics and static property. When the parameters or structure of plant is changed, a fuzzy controller with nonlinear scaling factors can maintain good performance indicators through re-tuning parameters and has stronger robustness.
Keywords :
fuzzy control; genetic algorithms; fuzzy controller; genetic algorithm; nonlinear scaling factors; optimizing parameters; parameters tuning; Control systems; Cybernetics; Fuzzy control; Fuzzy systems; Genetic algorithms; Machine learning; National electric code; Nonlinear control systems; Optimization methods; Steady-state; Fuzzy control; Genetic algorithm; Nonlinear scaling factors; Parameters tuning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370180
Filename :
4370180
Link To Document :
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