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A New Active Noise Control Algorithm That Requires No Secondary Path Identification Based on the SPR Property

机译:基于SPR特性的无需次级路径识别的新型主动噪声控制算法

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摘要

Active noise control (ANC) has been widely applied in industry to reduce environmental noise and equipment vibrations. Most available control algorithms require the identification of the secondary path, which increases the control system complexity, contributes to an increased residual noise power, and can even cause the control system to fail if the identified secondary path is not sufficiently close to the actual path. In this paper, based on the geometric analysis and the strict positive real (SPR) property of the filtered-x LMS algorithm, we introduce a new ANC algorithm suitable for single-tone noises as well as some specific narrowband noises that does not require the identification of the secondary path, though its convergence can be very slow in some special cases. We are able to extend the developed ANC algorithm to the case of active control of broadband noises through our use of a subband implementation of the ANC algorithm. Compared to other available control algorithms that do not require secondary path identification, our developed method is simple to implement, yields good performance, and converges quickly. Simulation results confirm the effectiveness of our proposed algorithm.
机译:主动噪声控制(ANC)已在工业中广泛应用,以减少环境噪声和设备振动。大多数可用的控制算法都需要识别辅助路径,这会增加控制系统的复杂性,导致残留噪声功率增加,如果识别出的辅助路径与实际路径的距离不够近,甚至可能导致控制系统发生故障。本文基于几何分析和Filtered-x LMS算法的严格正实(SPR)性质,我们引入了一种适用于单音噪声以及一些不需要降噪的特定窄带噪声的ANC新算法虽然在某些特殊情况下其收敛速度可能非常慢,但仍无法识别次级路径。通过使用ANC算法的子带实现,我们可以将开发的ANC算法扩展到主动控制宽带噪声的情况。与其他不需要辅助路径识别的可用控制算法相比,我们开发的方法易于实现,产生良好的性能并且收敛迅速。仿真结果证实了所提算法的有效性。

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