DocumentCode
3019286
Title
Control chaotic systems based on BP neural network with a new perturbation
Author
Zong, Xiao-ping ; Geng, Jun
Author_Institution
Coll. of Electron. & Inf. Eng., Hebei Univ., Baoding, China
fYear
2009
fDate
12-15 July 2009
Firstpage
166
Lastpage
170
Abstract
A new perturbation model is proposed, and used to train BP neural network for chaotic systems in this paper. The method requires no previous knowledge about the system to be controlled, including the dimensionality of the system and location of unstable fixed points, can be extended to other chaos control. It was tested on the Henon and Logistic maps, and the simulation results showed that it could make the chaos present periodic motion.
Keywords
backpropagation; chaos; neurocontrollers; nonlinear control systems; perturbation techniques; BP neural network; control chaotic system; logistic map; perturbation model; system dimensionality; unstable fixed point; Artificial neural networks; Chaos; Control systems; Information analysis; Motion control; Neural networks; Nonlinear control systems; Pattern analysis; Pattern recognition; Wavelet analysis; BP neural networks; Chaos control; Chaotic system; Periodic motion;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3728-3
Electronic_ISBN
978-1-4244-3729-0
Type
conf
DOI
10.1109/ICWAPR.2009.5207408
Filename
5207408
Link To Document