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
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