A study on an active noise canceller by using decomposed narrow-band signals

In many fields of active noise control (ANC), the filtered-x least mean squares (LMS) algorithm and its relatives are popular ones, because of their simplicity. In these algorithms, the input signal to the algorithms is the signal filtered by the plant model, which must be identified in advance. As well known, the usage of the filtered signal causes two major problems: the delay between adaptive FIR filter and the error signal; the well known eigenvalue spread in the autocorrelation matrix. In this article, the active noise control is proposed for specific applications such as ventilation equipment with a duct. The reference signal is decomposed into plural narrow-band signals by estimating each resonant frequency. As this approximation leads to that frequency characteristics of the plant model around vicinity of resonant frequencies are only taken account, there is no need to identify the overall characteristics of the plant model in advance. In the proposed method, lower order adaptive filters are only needed to adjust to the plant model with on-line manner. Finally, it is shown that the proposed method has almost the same performance as the filtered-x LMS algorithm with much less computational load