Convergence analysis of narrow-band active noise control system

Kuo, Sen M.; Tahernehadi, M.; Wang, Hao

doi:10.1109/82.752958

Cited by 40 publications

(13 citation statements)

References 9 publications

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“…A solution for case 1 was proposed by Kuo et al 9,10 The solution is most applicable for stationary multiple frequency single channel control where the fundamental and harmonics are internally generated. A general solution for case 2 is presented in this paper as the eigenvalue equalization filtered-x least mean squares ͑EE-FXLMS͒ algorithm.…”

Section: Eigenvalue Equalizationmentioning

confidence: 99%

Eigenvalue equalization filtered-x algorithm for the multichannel active noise control of stationary and nonstationary signals

Thomas

Lovstedt

Blotter

et al. 2008

The Journal of the Acoustical Society of America

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Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

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Section: Eigenvalue Equalizationmentioning

confidence: 99%

Eigenvalue equalization filtered-x algorithm for the multichannel active noise control of stationary and nonstationary signals

Thomas

Lovstedt

Blotter

et al. 2008

The Journal of the Acoustical Society of America

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“…They also developed three approaches to achieve that, including adjusting the positions of the secondary sources and the error sensors, increasing the number of secondary sources, and adding an inverse filter of the secondary path. In addition, Kuo et al [22] suggested that the amplitude of the reference signals should be chosen to be inversely proportional to the magnitude response of the secondary path at the corresponding frequency. While these approaches work, they either increase the complexity of the control algorithm or are only effective for specific applications.…”

Section: Introductionmentioning

confidence: 99%

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

Duan¹,

Li²,

Lim

et al. 2013

Journal of Vibration and Acoustics

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An enhanced multiple-input multiple-output (MIMO) filtered-x least mean square (FXLMS) algorithm using improved virtual secondary path is proposed as the basis for an active noise control (ANC) system for treating vehicle powertrain noise. This new algorithm is developed to overcome the limitation caused by the frequency-dependent property of the standard FXLMS algorithm and to reduce the variation of convergence speed inherent in multiple-channel cases, in order to improve the overall performance of the control system. In this study, the convergence property of the proposed algorithm is analyzed in the frequency domain in order to yield a better understanding of the physical meaning of the virtual secondary path. In practice, because of the arrangement and sensitivities of the actuators (speakers), transducers (microphones), and physical environment, the magnitude response of the main secondary paths can be very different from each other. This difference will cause difficulty in the overall convergence of the algorithm, which will result in minimal attenuation at some of the channels. The proposed channel equalized (CE) virtual secondary path algorithm is designed to tackle this difficulty by equalizing the mean magnitude level of the main secondary paths and by adjusting other secondary paths correspondingly to keep the coupling effects among the control channels unchanged. The performance of the proposed algorithm is validated by analyzing a two-input two-output active powertrain noise control system.

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“…It was shown that the phase error has a complex effect on the stability of the algorithm which is difficult to predict. Kuo et al [5] studied the eigenvalue spread of the reference signal's covariance matrix of narrowband FXLMS algorithm, which determines the convergent process. Vicente et al [6] analyzed the narrowband FXLMS algorithm based on the root-locus theory and derived an exact value of the maximum step size.…”

Section: Introductionmentioning

confidence: 99%

“…Vicente et al [6] analyzed the narrowband FXLMS algorithm based on the root-locus theory and derived an exact value of the maximum step size. But in both [5] and [6], only perfect secondary path models were considered so that the influence of modeling errors was not discussed. A special narrowband FXLMS-based algorithm with only two coefficients in the controller was proposed by Xiao et al [7,8] and Zhao et al [9], whose convergent properties were also analyzed in detail.…”

Section: Introductionmentioning

confidence: 99%

Novel convergence analysis of narrowband FXLMS-based algorithm

An¹,

Sun²,

Li³

2012

International Conference on Automatic Control and Artificial Intelligence (ACAI 2012)

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This paper presents a novel convergence analysis of the narrowband active noise/vibration system with FXLMS-based algorithm. It is revealed that the convergent behaviour mainly depends on the phase error of the secondary path model as well as the structure of the controller. With a constant step size, the convergent speed of the algorithm is maximized at a critical value of the phase error. The algorithm exhibits different convergent behaviours if the phase error is below or above this critical value, respectively. The theoretical analysis is validated by numerical simulations.

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Convergence analysis of narrow-band active noise control system

Cited by 40 publications

References 9 publications

Eigenvalue equalization filtered-x algorithm for the multichannel active noise control of stationary and nonstationary signals

Eigenvalue equalization filtered-x algorithm for the multichannel active noise control of stationary and nonstationary signals

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

Novel convergence analysis of narrowband FXLMS-based algorithm

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