Robust Auxiliary-Noise-Power Scheduling in Active Noise Control Systems With Online Secondary Path Modeling

Ahmed, Shakeel; Akhtar, Muhammad Tahir; Zhang, Xi

doi:10.1109/tasl.2012.2234112

Cited by 54 publications

(36 citation statements)

References 18 publications

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“…The filter W 1 ðzÞ in the proposed algorithm is also selected as an FIR filter of tap-weight length 192. Proposed-I: Using DR-algorithm of (24), compute w 1 ðn þ 1Þ; Proposed-II: Using DR-algorithm of (25), compute w 1 ðn þ 1Þ; wðn þ 1Þ ¼ w 1 ðn þ 1Þ; end while 2 The SPM filter b SðzÞ can be obtained by offline measurements [7], and/or may be adapted during the online operation of ANC system (see [24] and references there in). We assume that b SðzÞ % SðzÞ is available offline, and in fact the online SPM is beyond the scope of this paper.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Data-reusing-based filtered-reference adaptive algorithms for active control of impulsive noise sources

Akhtar

Akinori

2015

Applied Acoustics

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Data-reusing-based filtered-reference adaptive algorithms for active control of impulsive noise sources

Akhtar

Akinori

2015

Applied Acoustics

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“…6 The overall modeling algorithm (OMA) 1 and the auxiliary noise strategy are compared in the work of Bao et al 7 In the work of the aforementioned authors, 8 an extra filter is used to remove the primary noise signal from the adaptation of the SP and in the work of Kuo and Vijayan, 9 the same is done but using a predictor filter. Other related strategies are proposed in the work of Ahmed et al 14 The simultaneous equation method is proposed in the work of Fujii and Ohga. Selection of the auxiliary noise signal level by using the SP estimate and making it R times lower than the residual noise signal is proposed in the work of Carini and Malatini 12 and in the work of Lopes and Gerald, 13 the value of R is adapted as required.…”

Section: State-of-the-artmentioning

confidence: 99%

“…(11) p 0 = from the periodogram (12) p(0) = w(0) =p 0 (13) q j (0) = 1 (14) = small number (15) If the controller of the MFxLMS (w 1,i ) has a significantly larger magnitude than the controller of MMFxLMS (w 2,i ), then this probably means that an incorrectly modeled SP is leading the MFxLMS to divergence.…”

Section: Fxlms Algorithmmentioning

confidence: 99%

“…Selection of the auxiliary noise signal level by using the SP estimate and making it R times lower than the residual noise signal is proposed in the work of Carini and Malatini 12 and in the work of Lopes and Gerald, 13 the value of R is adapted as required. Other related strategies are proposed in the work of Ahmed et al 14 The simultaneous equation method is proposed in the work of Fujii and Ohga. 15 Chang et al 16,17 propose to decouple estimation of the SP at different frequencies for narrowband ANC.…”

Section: State-of-the-artmentioning

confidence: 99%

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A narrowband active noise control system with reference synthesis

Lopes

Gerald

2019

Adaptive Control & Signal

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Most active noise control (ANC) algorithms require a model of the secondary path (SP). If there are large changes in the SP, online SP modeling algorithms may not be able to follow the changes quickly enough to prevent divergence. In this work, the mirror-MFxLMS (MMFxLMS) is adapted to narrowband ANC, and the resulting algorithm is analyzed. The MMFxLMS is an algorithm similar to the MFxLMS and FxLMS but has online SP modeling; it is stable for any SP estimate and does not require auxiliary noise. In addition, a technique to alternate between MFxLMS and MMFxLMS is proposed, resulting in the M 3 FxLMS algorithm, which does not sacrifice performance and assures stability. However, the M 3 FxLMS requires a reference signal that is not available in feedback ANC.Feedback ANC is important in many practical cases, for instance, in ANC headphones. To solve this problem, a technique is proposed to synthesize a reference formed by a sum of sinusoids using measurements from the error sensor signal.This technique uses the fast Fourier transform to obtain estimates of the harmonic frequencies of the periodic noise components, and then refines and tracks these using a phase-locked loop (PLL). The resulting algorithm enables a stable ANC system, even under large and sudden changes in the SP. The proposed PLL is also new and has a lock-in range equal to the full band of the system. KEYWORDS active noise control (ANC), feedback, FxLMS, narrowband, PLL, stability INTRODUCTIONActive noise control (ANC) is a technique where waves (antinoise) with opposite phase to a noise signal are used to reduce the noise signal level. 1 In feedforward ANC, a signal called the reference signal is used to generate the antinoise signal, using additional information from a set of error sensors that indicates the residual noise level. In feedback ANC, the signal from a set of error sensors is used to generate the antinoise signal. In narrowband ANC, the noise to be canceled is assumed to be periodic or a sum of periodic signals. This paper addresses single-channel (one error sensor) narrowband feedback ANC, with applications, for instance, in ANC headphones.Most ANC algorithms require a secondary path (SP) model and can become unstable if that model is not sufficiently accurate. The SP model can be obtained before the start of noise canceling (offline) or during operation (online). If the SP changes significantly during noise cancelation, online SP modeling is required. However, even with online SP modeling, if there is a large and sudden change, the model may not be updated quickly enough and the algorithm may become unstable. To solve this problem, the authors have previously proposed the mirror-MFxLMS (MMFxLMS) algorithm. 2 1118

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“…Nevertheless, the fixed power auxiliary noise contributes to the residual error, which we want to minimize, and leads to the performance degradation of the ANC system in the steady state. To remedy this problem, various auxiliary noise power scheduling strategies have been proposed [20][21][22][23][24][25]. However, it should be noted that most of the above mentioned strategies were designed for broadband active noise control (BANC).…”

Section: Introductionmentioning

confidence: 99%

A New Online Secondary Path Modeling Method with An Auxiliary Noise Power Scheduling Strategy for Narrowband Active Noise Control Systems

et al. 2017

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Abstract:In recent years, the online secondary path modeling (SPM) method with an auxiliary noise power scheduling strategy has been crucial for active noise control (ANC) systems and has also become a popular research topic. However, most scheduling strategies have been designed for broadband active noise control (BANC), and these ideas may not be directly applied to narrowband active noise control (NANC) systems due to the difference in structure between BANC and NANC systems. In this paper, a new online SPM method with auxiliary noise power scheduling is proposed. Here, the controlled system is adapted using the filtered-x weighted accumulated least mean square (FXWALMS) algorithm proposed by the authors. Moreover, the auxiliary noise power is scheduled based on the convergence status of the forgetting factor to accurately track the change in the NANC system. As a result, the proposed method not only achieves good modeling accuracy and fast convergence but also considerably increases noise attenuation. Extensive simulations are conducted to prove the superior performance of the proposed method in various scenarios.

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Robust Auxiliary-Noise-Power Scheduling in Active Noise Control Systems With Online Secondary Path Modeling

Cited by 54 publications

References 18 publications

Data-reusing-based filtered-reference adaptive algorithms for active control of impulsive noise sources

Data-reusing-based filtered-reference adaptive algorithms for active control of impulsive noise sources

A narrowband active noise control system with reference synthesis

A New Online Secondary Path Modeling Method with An Auxiliary Noise Power Scheduling Strategy for Narrowband Active Noise Control Systems

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