Active Noise Control System Based on Hybrid Fixed Filter Method and FxLMS Algorithm

Traditional real-time active noise control (ANC) has been widely used to reduce environmental noise, usually using the filtered-x least mean square (FxLMS) algorithm to adjust the control filter coefficients. However, the adaptive algorithm converges slowly, cannot achieve stable noise reduction effect immediately, and may diverge under the interference of transient noise. Therefore, this paper proposes a method that combines fixed filter coefficients with FxLMS algorithm to overcome the problem of slow convergence speed of FxLMS algorithm and improve the robustness of adaptive algorithm. The algorithm selects pre-trained control filter coefficients according to the spectrum of noise source, and at the same time, FxLMS algorithm updates the control filter coefficients with the filter coefficients as initial values. Experimental results show that this algorithm can effectively reduce convergence time and improve robustness.