Title: Adaptive active noise control with online secondary path modelling and variable step-size learning

Authors: Nguyen Le Thai; Xing Wu; Jing Na; Yu Guo; Nguyen Thi Trung Tin; Phan Xuan Le

Addresses: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Electric and Electronic Engineering, Tuy Hoa Industrial College, Tuy Hoa 620900, Vietnam ' Faculty of Electric and Electronic Engineering, Tuy Hoa Industrial College, Tuy Hoa 620900, Vietnam

Abstract: The performance of conventional filtered-X least mean squares (FXLMS)-based active noise control (ANC) systems may degrade owing to uncertainties in the secondary path model and constant learning gains (step-size parameters) used in the FXLMS algorithms. In this paper, a new ANC feedforward system design with online secondary path modelling and variable step-size parameters (VSSPs) is proposed. To improve the convergence performance of FXLMS algorithms, an online tuning scheme of step-size parameters (or learning gains) for the adaptive learning is developed based on the residual errors. In particular, this paper shows how to analyse the stability of the proposed closed-loop ANC systems and to study the convergence of the presented adaptations. Moreover, a modified online modelling strategy is introduced to address the modelling of secondary path dynamics. The modelling and adaptive control are all online implemented without any offline learning phase; faster convergence and better noise elimination can be achieved. Appropriate comparisons to other methods and their computational complexities are also investigated. Comparative simulation results illustrate the improved performance of the proposed methods.

Keywords: active noise control; ANC; filtered-X least mean square; FXLMS; variable step-size learning; adaptive control; secondary path modelling; uncertainty; online tuning; step-size parameters; learning gains; adaptive learning; residual errors; simulation.

DOI: 10.1504/IJMIC.2016.075278

International Journal of Modelling, Identification and Control, 2016 Vol.25 No.2, pp.71 - 84

Received: 15 Jun 2015
Accepted: 21 Jul 2015
Published online: 09 Mar 2016 *

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