RBF Network In The System Of AANC

Noise impact on human health has been a widespread concern. Pipeline muffler has been put forward to the factory, office, and other places. Passive damping technology is a traditional muffler technology, but only on the high frequency noise is good noise effects, it is very difficult to produce an effect of low frequency noise. Active Noise Control Technology based on this emerged as an effective noise control methods.Active Noise Control refers to the formation of sub-human noise to offset a way of the original noise. Active Noise Control in accordance with the basic principles of the same two frequencies, the acoustic phase will be fixed in cancellation of interference. AANC is accomplished by adaptive secondary source of the active noise control. AANC the heart of the system is adaptive filter and the corresponding adaptive algorithm. Adaptive filter can be set according to certain criteria in advance automatically adjust its own transfer function to achieve the required output. Adaptive filter design can not know in advance the statistical characteristics of the input, but also in the process of filtering the input statistical characteristics such as intercropping slow change at any time it can automatically adapt to. These highlight the advantages of it was logical to accept the Active Noise Control Institute and development.This paper uses the theory of neural network controller has been optimized design, the controller design, select the appropriate network model and the proliferation of constant, function approximation ability will have a positive impact. By RBF (Radial Basis Function), the new controller not only overcome the BP network design needs default initial value problems, and has further enhanced the one-dimensional input output training speed. RBF network, the use of arbitrary precision approximating function of the ability of a controller transfer function approximation, the importation of samples for training to the extent possible, should be the ideal transfer function output. RBF for the characteristics of the network, the controller with RBF network for the transfer function approximation, can take the better output, thereby raising the robustness of the system purposes. The simulation results show that, using the controller RBF network design, the active noise control system robustness have been significantly improved.