DocumentCode :
3331174
Title :
Fuzzy RBF neural network in the application of magnetic levitation system
Author :
Jing Zhang ; Sai Dai ; Jiamin Li ; Ning Wang
Author_Institution :
Dept. of Autom., Harbin Univ. of Sci. & Technol., Harbin, China
Volume :
2
fYear :
2011
fDate :
22-24 Aug. 2011
Firstpage :
990
Lastpage :
994
Abstract :
To solve the problems that magnetic levitation system has the characteristics of open-loop instability and nonlinearity and the traditional PID controller is difficult to achieve good control effect because of the fixed parameters, a kind of intelligent PID control system based on fuzzy RBF neural network is proposed in this paper. This method combines the reasoning ability of fuzzy control with study ability of neural network. Fuzzy control and RBF neural network are applied in order to adjust the parameters of PID kp, ki and kd online which is to satisfy the static and dynamic performance requirements in magnetic levitation system. By comparing with the conventional PID control, the results showed that, the improved control has better adaptability and robustness which can control magnetic levitation system more effectively.
Keywords :
control nonlinearities; fuzzy control; fuzzy neural nets; intelligent control; magnetic levitation; neurocontrollers; radial basis function networks; stability; three-term control; fuzzy RBF neural network; fuzzy control reasoning ability; intelligent PID control system; magnetic levitation system; neural network study ability; nonlinearity characteristics; open-loop instability characteristics; radial basis function network; Control systems; Equations; Fuzzy control; Magnetic levitation; Mathematical model; Steel; Tuning; PID control; fuzzy RBF network; magnetic levitation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Strategic Technology (IFOST), 2011 6th International Forum on
Conference_Location :
Harbin, Heilongjiang
Print_ISBN :
978-1-4577-0398-0
Type :
conf
DOI :
10.1109/IFOST.2011.6021187
Filename :
6021187
Link To Document :
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