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 acontroller filter. Researchers tend to improve performance of ANC systems by enhancing andmodifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANCapplications an online secondary path modelling method using a white noise as a training signal isrequired to ensure convergence of the system. This paper also proposes a new approach for onlinesecondary path modelling in feedfoward ANC systems. The proposed algorithm is designed in a waythat the injection of white noise is stopped at the optimum point, when the modelling accuracy issufficient. In this approach, a sudden change in secondary path during the operation makes thealgorithm to reactivate injection of the white noise to adjust the secondary path estimation. Benefitingnew version of the FxLMS algorithm and not a continual injection of white noise during systemoperation makes the proposed system more desirable, also improves the noise attenuation andconvergence rate. Comparative simulation results shown in this paper indicate effectiveness of theproposed approach.