Abstract
The adaptive active noise control problem is considered, in which the response of the system under control varies with time. A new algorithm for system identification in such circumstances, using multiple models of the secondary path transfer function, is presented. The computational burden of the proposed algorithm can be much smaller than the existing methods, particularly in the multi-channel case. An infinite impulse response structure is assumed for the control filter, and the recursive least mean square algorithm introduced by Feintuch is used to adjust the filter coefficients. By combining the proposed identification technique and the filtered-x recursive least mean square algorithm, the multiple model adaptive controller for active noise control problems is presented. This method requires a prioriinformation about the plant to select models of the secondary path transfer function, so it can be used when we have some information on the plant and operating situations. Computer simulations were performed to show the effectiveness of the proposed algorithm in a simple duct problem.
Published Version
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