Fast Adaptive Algorithms for Active Control of Nonlinear Noise Processes

Active noise control problems are often affected by nonlinear effects such as distortion and saturation of measurement and actuation devices, which call for suitable nonlinear models and algorithms. The active noise control problem can be interpreted as an indirect model identification problem, due to the secondary path dynamics that follow the control filter block. This complicates the weight update mechanism in the nonlinear case, in that the error gradient depends on the secondary path gradient through nonlinear recursions. A simpler and computationally less demanding approach is here proposed that employs the updating scheme of the standard filtered-x least mean squares (LMS) or filtered-u LMS algorithm. As in those schemes, the calculation of the error gradient requires a signal filtering through an auxiliary system, here obtained through a secondary adaptation loop. The resulting dual filtering LMS algorithm performs the adaptation of the controller parameters in a direct identification mode and can therefore be easily coupled with adaptive model structure selection schemes to provide online tuning of the model structure, for improved model robustness.

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“…1428 D. DELVECCHIO AND L. PIRODDI employing once again the approximation (11). Notice that the last sum operator is extended only to the y.…”

Section: Nanc Methods For Nonlinear Secondary Pathsmentioning

confidence: 99%

A dual filtering scheme for nonlinear active noise control

Delvecchio

Piroddi

2013

Adaptive Control & Signal

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“…It has been demonstrated that the FxLMS algorithm gives very poor performance in the case of nonlinear processes (Strauch & Mulgrew, 1998). For efficient algorithms for ANC of non linear source, see (Reddy et al, 2008) and references there in. In many practical situations, it is desirable to shift the quiet zone away from the location of error microphones to a virtual location where error microphone cannot be installed (Bonito et al, 1997).…”

Section: Review On Signal Processing Challengesmentioning

confidence: 99%

Applications of Adaptive Filtering: Recent Advancements in Active Noise Control

Tahir¹,

Mitsuhashi²,

Akinori³

2011

Adaptive Filtering Applications

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“…This in turn restricts the efficacy of ANC to frequencies less than half of its sampling frequency. A number of researchers have shown interest in developing computationally efficient algorithms, otherwise known as fast ANC algorithms [10][11][12][13][14][15][16][17][18]. A class of fast ANC algorithms known as the block algorithm, which exploits frequency-domain convolution and correlation operations, has been shown to achieve a significant computational advantage over its conventional time-domain counterpart [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

A computationally efficient frequency-domain filtered-X LMS algorithm for virtual microphone

Das

Moreau

Cazzolato

2013

Mechanical Systems and Signal Processing

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The computational complexity of the virtual FXLMS algorithm is higher than that of the conventional FXLMS algorithm. The additional complexity comes from computation of three secondary path transfer functions (as opposed to one) and a transfer function between the physical and the virtual microphones. The order of these transfer functions may be very high in practical situations where the acoustic damping is low. The high computational complexity of the virtual FXLMS algorithm imposes issues like high power consumption, making it difficult to implement the algorithm in battery operated ANC devices such as active headsets. In addition, the operating sampling frequency of the algorithm is limited and this in turn restricts its operation to relatively low frequency applications. In this paper, a new virtual FXLMS algorithm is derived by implementing all of the secondary path transfer functions in the frequency domain. The algorithm is simulated using measured transfer functions in a duct with low acoustic damping. Implementation schemes are proposed for the new frequency-domain virtual FXLMS algorithm, citing its advantages for use as an efficient real-time active noise control algorithm.Index Terms: Active noise control, adaptive filter, frequency-domain adaptive filter, computational complexity, virtual ANC. 2

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Fast Adaptive Algorithms for Active Control of Nonlinear Noise Processes

Cited by 48 publications

References 12 publications

A dual filtering scheme for nonlinear active noise control

A dual filtering scheme for nonlinear active noise control

Applications of Adaptive Filtering: Recent Advancements in Active Noise Control

A computationally efficient frequency-domain filtered-X LMS algorithm for virtual microphone

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