DocumentCode :
2150886
Title :
Design of ball and beam system controller based on kernel function principal component analysis
Author :
Zhong, Bing-xiang ; Li, Tai-fu
Author_Institution :
College of Electronic Information Engineering, Chongqing University of science and technology, 401331, China
fYear :
2010
fDate :
4-6 Dec. 2010
Firstpage :
5055
Lastpage :
5058
Abstract :
To simulate the actions of human, in this paper a controller of the ball and beam system has been designed based on kernel function principal component analysis (KPCA). The sampling data were acquired by controlling ball and beam system manually, the time sequence of embedded dimensionality were determined by fault nearest neighbours dot algorithm, their features were extracted in the space of nonlinear supporting variable through KPCA algorithm and phase-space are reconstructed, then the linear regression were realized by the least square method and mathematical model was built. Experiments indicated that the controller was effective. It can simulate the behavior of human and possesses high precision and stability.
Keywords :
Artificial neural networks; Control systems; Feature extraction; Fuzzy neural networks; Kernel; Principal component analysis; KPCA; ball and beam system; embedded dimensionality; phase-space reconstruction; system modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
Type :
conf
DOI :
10.1109/ICISE.2010.5691365
Filename :
5691365
Link To Document :
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