Effects of Online Secondary Path Modeling on Anc Systems

In Active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a auxiliary noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a auxiliary noise with a larger variance is used. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in FX-LMS based ANC systems. The proposed FXLMS algorithm uses the advantages of auxiliary noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.