New FIR filter-based adaptive algorithms incorporating with commutation error to improve active noise control performance

• Published in: Automatica (Oxford) Vol. 43; no. 2; pp. 325 - 331
• Main Authors: Liao, Ching-Wen, Lin, Jong-Yih
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.02.2007; Elsevier
• Subjects: Acoustics; Active noise control; Adaptive algorithms; Applied sciences; Commutation error; Computer science; control theory; systems; Control theory. Systems; Convergence speed; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Finite impulse response filters; Fundamental areas of phenomenology (including applications); Information, signal and communications theory; Noise: its effects and control; Physics; Residual error; Signal and communications theory; Signal, noise; Telecommunications and information theory; Commutation error; Finite impulse response filters; Residual error; Adaptive algorithms; Active noise control; Convergence speed; Active noise control: Commutation error; Adaptive algorithm; Noise reduction; Adaptive filter; Noise control; Noise level; Speed reducer; White noise; Finite impulse response filter; Numerical convergence
• ISSN: 0005-1098; 1873-2836
• DOI: 10.1016/j.automatica.2006.08.019

This study considers a commutation error (CE) that results from a difference associated with the altered sequence in real active noise control (ANC) applications as compared with that at the derivation stage. New adaptive algorithms are developed as FxLMS/CE, FxNLMS/CE and FxRLS/CE in an aim to eliminate the CE-associated disturbance and to liberate the restriction of slow adaptation imposed on the existing adaptive algorithms in the ANC applications. Computer simulations show that the rate of convergence is greatly improved for the new adaptive algorithms as compared with that of the conventional algorithms. In parallel with the improved rate of convergence, simulations exhibit efficient ANC performance for all CE-based algorithms. The best ANC performance is seen for FxRLS/CE algorithm that can acquire ∼ 2 s of convergence rate and ∼ 34 dB reduction of sound pressure level for band-limited white noise. All experimental results indeed demonstrate enhanced ANC performance; the FxNLMS/CE algorithm can acquire ∼ 2 s of convergence rate and ∼ 20 dB reduction of sound pressure level for band-limited white noise. Our data together support the effectiveness to include CE into the FIR filter-based adaptive algorithms for superior ANC performance with respect to the convergence speed and noise reduction level.