A Robust Feedforward Active Noise Control System with a Variable Step-size Fxlms Algorithm: Designing a New Online Secondary Path Modelling Method

Several approaches have been introduced in literature for active noise control (ANC) systems. Since Filtered-x-Least Mean Square (FxLMS) algorithm appears to be the best choice as a controller filter. Researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm is designed in a way that the injection of white noise is stopped at the optimum point, when the modelling accuracy is sufficient. In this approach, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to adjust the secondary path estimation. Benefiting new version of the FxLMS algorithm and not a continual injection of white noise during system operation makes the proposed system more desirable, also improves the noise attenuation and convergence rate. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach.