DocumentCode :
1692774
Title :
A novel active noise control using neural networks without the secondary path identification
Author :
Zhang, Xinghua ; Ren, Xuemei
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
fYear :
2010
Firstpage :
5037
Lastpage :
5041
Abstract :
In this paper, a novel active noise control (ANC) scheme based on neural networks is presented for nonlinear ANC systems without the identification of secondary path by introducing virtual primary noises. The ANC system is analyzed in the form of discrete-time state equations. The proposed controller employs neural networks to attenuate the noises. The proposed scheme does not require the dynamical knowledge of the primary and secondary path model compared to classical ANC approaches. The stability of the proposed scheme is analyzed by the Lyapunov theory. Simulation results show that the proposed strategy performs well for attenuating the noises.
Keywords :
Lyapunov methods; active noise control; discrete time systems; neurocontrollers; nonlinear control systems; stability; Lyapunov theory; active noise control; discrete-time state equation; neural network; noise attenuation; nonlinear ANC system; stability; virtual primary noise; Adaptation model; Adaptive systems; Algorithm design and analysis; Artificial neural networks; Equations; Mathematical model; Noise; Nonlinear active noise control; discrete-time; identification of secondary path; virtual primary noises;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554646
Filename :
5554646
Link To Document :
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