基于权重优化AF的非线性主动噪声控制算法

doi:10.13229/j.cnki.jdxbgxb.20240294

摘要/Abstract

摘要：

非线性噪声普遍具有不确定性高、频谱特性难以精确描述、稳态误差较大以及瞬态性能差等特点，如何对非线性噪声进行有效控制是一个具有挑战性的任务，为此本文提出基于权重优化AF的非线性主动噪声控制算法。该算法采用基准信号的正余弦分量进行直接频率分析，分析一次噪声和窄带频率范围，得到准确的噪声估计结果，提高了噪声控制的精度和效果。通过对非线性主动噪声估计结果进行训练，调整自适应滤波器的权重，实现对期望输出信号的重构，从而有效抑制了非线性噪声的影响，提高了控制效果。实验结果表明：该算法下信号噪声的均方误差较低、稳态误差小，能够适应各种复杂的噪声环境，有效改善了噪声控制的质量，具有较高的实用性和可靠性。

关键词: 权重优化, 自适应滤波器, 窄带噪声, 噪声估计, 非线性主动噪声

Abstract:

Nonlinear noise generally has high uncertainty， difficult to accurately describe spectral characteristics， large steady-state errors， and poor transient performance. Effective control of nonlinear noise is a challenging task. Therefore， a nonlinear active noise control algorithm based on weight optimization AF is proposed. This algorithm uses the sine and cosine components of the reference signal for direct frequency analysis， analyzes the primary noise and narrowband frequency range， obtains accurate noise estimation results， and improves the accuracy and effectiveness of noise control. By training the results of nonlinear active noise estimation and adjusting the weights of the adaptive filter， the reconstruction of the expected output signal is achieved， effectively suppressing the influence of nonlinear noise and improving the control effect. The experimental results show that under this algorithm， the mean square error of signal noise is low and the steady-state error is small， which can adapt to various complex noise environments and effectively improve the quality of noise control， it has high practicality and reliability.

Key words: weight optimization, adaptive filter, narrowband noise, noise estimation, nonlinear active noise

中图分类号:

TP273

赵男男,金凤,丁宏钰. 基于权重优化AF的非线性主动噪声控制算法[J]. 吉林大学学报(工学版), 2025, 55(5): 1722-1727.

Nan-nan ZHAO,Feng JIN,Hong-yu DING. Nonlinear active noise control algorithm based on weighted optimization AF[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(5): 1722-1727.

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