Active Noise Feedback Control Using a Neural Network
Autor: | Jia Yongle, Zhang Qizhi |
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Jazyk: | angličtina |
Rok vydání: | 2001 |
Předmět: |
Engineering
Noise power business.industry Mechanical Engineering Filter (signal processing) Geotechnical Engineering and Engineering Geology Condensed Matter Physics Noise shaping lcsh:QC1-999 Adaptive filter Noise Mechanics of Materials Control theory Control system Kernel adaptive filter Electronic engineering business lcsh:Physics Civil and Structural Engineering Active noise control |
Zdroj: | Shock and Vibration, Vol 8, Iss 1, Pp 15-19 (2001) |
ISSN: | 1875-9203 1070-9622 |
Popis: | The active noise control (ANC) is discussed. Many digital ANC systems often based on the filter-x algorithm for finite impulse response (FIR) filter use adaptive filtering techniques. But if the primary noise path is nonlinear, the control system based on adaptive filter technology will be invalid. In this paper, an adaptive active nonlinear noise feedback control approach using a neural network is derived. The feedback control system drives a secondary signal to destructively interfere with the original noise to cut down the noise power. An on-line learning algorithm based on the error gradient descent method was proposed, and the local stability of closed loop system is proved using the discrete Lyapunov function. A nonlinear simulation example shows that the adaptive active noise feedback control method based on a neural network is very effective to the nonlinear noise control. |
Databáze: | OpenAIRE |
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