Self-adapting variable step size strategies for active noise control systems with acoustic feedback

被引：10

作者：

Aslam, Muhammad Saeed ^{[1
]}

Shi, Peng ^{[1
]}

Lim, Cheng-Chew ^{[1
]}

机构：

[1] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia

来源：

AUTOMATICA | 2021年 / 123卷

关键词：

Parameter estimation; FxLMS; Online feedback path estimation; Self-adapting variable step size; Active noise control; AUXILIARY NOISE; ALGORITHMS;

D O I：

10.1016/j.automatica.2020.109354

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Self-adapting variable step size (SAVSS) normalized least mean square (NLMS) algorithms are derived and analysed for the active noise control systems with acoustic feedback path. The objective of the proposed SAVSS scheme is to resolve the conflicting requirements of rapid convergence and low misadjustment. A tuningless power scheduling scheme is proposed that varies the gain according to the output of the predictor filter, and switches to a low gain on the basis of a minimum criteria. In the steady state, a low gain auxiliary noise significantly improves noise reduction performance, and the update of the feedback compensation filter and predictor filter is discontinued to reduce computations. Simulations are performed with narrowband noises to validate the improved performance of the proposed method in comparison with established state-of-the-art methods. (c) 2020 Elsevier Ltd. All rights reserved.

引用

页数：9

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