A Novel Feedforward Hybrid Active Noise Control System with Narrowband Frequency Adaptive Estimation and Error Separation

The conventional feedforward hybrid active noise control （FFHANC） system combines the advantages of the feedforward narrowband active noise control （FFNANC） system and the feedforward broadband active noise control （FFBANC） system. To enhance its adaptive adjustment capability under frequency mismatch （FM） conditions， this paper introduces a narrowband frequency adaptive estimation module into the conventional FFHANC system. This module integrates an autoregressive （AR） model and a linear cascaded adaptive notch filter （LCANF）， enabling accurate reference signal frequency estimation even under significant FM. Furthermore， in order to improve the coherence between narrowband and broadband components in the system’s error signal and its corresponding control filter for the conventional FFHANC system， this paper proposes an algorithm based on autoregressive bandpass filter bank （AR-BPFB） for error separation. Simulation results demonstrate that the proposed FFHANC system maintains robust performance under high FM conditions and effectively suppresses hybrid-band noise. The AR-BPFB algorithm significantly elevates the convergence speed of the FFHANC system.