Adaptive Laguerre filters for active noise control

Feedforward controllers are used in many active noise control (ANC) systems to generate destructive interference in noise fields. An ideal feedforward ANC controller should have an infinite impulse response (IIR) transfer function, but most available feedforward ANC controllers have finite impulse responses (FIR) instead. The main reason is related to the adaptation algorithms of ANC systems. In general, adaptive FIR filters converge faster with guaranteed stability. In this study, the adaptive Laguerre filter is proposed and tested in an ANC application with positive experimental effects. The new ANC controller is an IIR filter, but its adaptation is similar to that of a FIR filter with fast convergence and guaranteed stability. Detailed explanations and analysis are presented in the main text.     

Lattice form adaptive infinite impulse response filtering algorithm for active noise control

In some situations of active noise control, infinite impulse response (IIR) filters are more suitable than finite impulse response (FIR) filters owing to the poles in the transfer function. A number of algorithms have been derived for applying IIR filters in active noise control; however, most of them use the direct form IIR filter structure, which faces the difficulties of checking stability and relatively slow convergence speed for noise composed of narrow-band components with large power disparity. To overcome these difficulties along with using the direct form IIR filters, a new adaptive algorithm is proposed in this paper, which uses and updates the lattice form adaptive IIR filter in an active noise control system. Full mathematical derivations of the proposed algorithm are presented, and the comparison between the proposed algorithm and the commonly used filtered-u LMS and filtered-v LMS algorithms shows the superiority of the proposed algorithm.     

Improving performance of FxRLS algorithm for active noise control of impulsive noise

Active noise control (ANC) systems employing adaptive filters suffer from stability issues in the presence of impulsive noise. New impulsive noise control algorithms based on filtered-x recursive least square (FxRLS) algorithm are presented. The FxRLS algorithm gives better convergence than the filtered-x least mean square (FxLMS) algorithm and its variants but lacks robustness in the presence of high impulsive noise. In order to improve the robustness of FxRLS algorithm for ANC of impulsive noise, two modifications are suggested. First proposed modification clips the reference and error signals while, the second modification incorporates energy of the error signal in the gain of FxRLS (MGFxRLS) algorithm. The results demonstrate improved stability and robustness of proposed modifications in the FxRLS algorithm. However, another limitation associated with the FxRLS algorithm is its computationally complex nature. In order to reduce the computational load, a hybrid algorithm based on proposed MGFxRLS and normalized step size FxLMS (NSS-FXLMS) is also developed in this paper. The proposed hybrid algorithm combines the stability of NSS-FxLMS algorithm with the fast convergence speed of the proposed MGFxRLS algorithm. The results of the proposed hybrid algorithm prove that its convergence speed is faster than that of NSS-FxLMS algorithm with computational complexity lesser than that of FxRLS algorithm.     

RETRACTED: A Hybrid Nonlinear Active Noise Control Method Using Chebyshev Nonlinear Filter

Investigations into active noise control (ANC) technique have been conducted with the aim of effective control of the low-frequency noise. In practice, however, the performance of currently available ANC systems degrades due to the effects of nonlinearity in the primary and secondary paths, primary noise and louder speaker. This paper proposes a hybrid control structure of nonlinear ANC system to control the non-stationary noise produced by the rotating machinery on the nonlinear primary path. A fast version of ensemble empirical mode decomposition is used to decompose the non-stationary primary noise into intrinsic mode functions, which are expanded using the second-order Chebyshev nonlinear filter and then individually controlled. The convergence of the nonlinear ANC system is also discussed. Simulation results demonstrate that proposed method outperforms the FSLMS and VFXLMS algorithms with respect to noise reduction and convergence rate.     

A relaxed condition for "perfect" cancellation of broadband noise in 3D enclosures

This paper presents a relaxed condition for "perfect" cancellation of broadband noise in 3D enclosures. On the basis of a truncated modal model, it can be shown that the primary and secondary paths belong to a same subspace if a certain condition is satisfied. There exists a finite impulse response (FIR) filter transfer function vector for perfect cancellation of the primary paths. The analytical result is verified numerically with an active noise control (ANC) system in a 3D rectangular enclosure. The proposed ANC scheme is shown to fit well into the framework of an existing multichannel least-mean squares (LMS) algorithm for adaptive implementation.     

A novel feedback active noise control for broadband chaotic noise and random noise

The feedback active noise control (ANC) can be seen as a predictor, the conventional method based on filtered-x least mean square (FXLMS) algorithm can only be useful for linear and tonal noise, but for nonlinear and broadband noise, it is useless. The feedback ANC using functional link artificial neural networks (FLANN) based on filtered-s least mean square (FSLMS) algorithm can reduce some nonlinear noise such as chaotic noise, but the noise cancellation performance is not very well, at the same time, it is not useful to random noise. To solve the problem above, a new feedback ANC using wavelet packet FXLMS (WPFXLMS) algorithm is proposed in this paper. By decomposing the broadband noise into several band-limited parts which are predictable and each part is controlled independently, the proposed algorithm can not only suppress the chaotic noise, but also mitigate the random noise. Compared with FXLMS and FSLMS algorithms, proposed WPFXLMS algorithm also holds the best performance on noise cancellation. Numerous simulations are conducted to demonstrate the effectiveness of the proposed WPFXLMS algorithm.     

Variable step-size based method for acoustic feedback modeling and neutralization in active noise control systems

This paper investigates the issue of the acoustic feedback during online operation of active noise control (ANC) systems. In the existing approach, two FIR filters are used for this task: adaptive for feedback path modeling (FBPM) and fixed for feedback neutralization (FBN). Previously, a simplified method is proposed where these two tasks of modeling and neutralization have been combined into one feedback path modeling and neutralization (FBPMN) adaptive filter. Here we introduce an intuition based variable step size (VSS) parameter, for LMS equation of FBPMN filter. This VSS is motivated from the fact that the error signal of FBPMN filter contains a disturbance-component that is decreasing in nature. The computer simulations are carried out for single-channel and multichannel ANC systems. It is demonstrated that the proposed method achieves better performance than the existing methods.     

Model independent control of lightly damped noise/vibration systems

Feedforward control is a popular strategy of active noise/vibration control. In well-damped noise/vibration systems, path transfer functions from actuators to sensors can be modeled by finite impulse response (FIR) filters with negligible errors. It is possible to implement noninvasive model independent feedforward control by a recently proposed method called orthogonal adaptation. In lightly damped noise/vibration systems, however, path transfer functions have infinite impulse responses (IIRs) that cause difficulties in design and implementation of broadband feedforward controllers. A major source of difficulties is model error if IIR path transfer functions are approximated by FIR filters. In general, active control performance deteriorates as model error increases. In this study, a new method is proposed to design and implement model independent feedforward controllers for broadband in lightly damped noise/vibration systems. It is shown analytically that the proposed method is able to drive the convergence of a noninvasive model independent feedforward controller to improve broadband control in lightly damped noise/vibration systems. The controller is optimized in the minimum H2 norm sense. Experiment results are presented to verify the analytical results.     

A nonlinear active noise control algorithm for virtual microphones controlling chaotic noise

In active noise control (ANC) systems, virtual microphones provide a means of projecting the zone of quiet away from the physical microphone to a remote location. To date, linear ANC algorithms, such as the filtered-x least mean square (FXLMS) algorithm, have been used with virtual sensing techniques. In this paper, a nonlinear ANC algorithm is developed for a virtual microphone by integrating the remote microphone technique with the filtered-s least mean square (FSLMS) algorithm. The proposed algorithm is evaluated experimentally in the cancellation of chaotic noise in a one-dimensional duct. The secondary paths evaluated experimentally exhibit non-minimum phase response and hence poor performance is obtained with the conventional FXLMS algorithm compared to the proposed FSLMS based algorithm. This is because the latter is capable of predicting the chaotic signal found in many physical processes responsible for noise. In addition, the proposed algorithm is shown to outperform the FXLMS based remote microphone technique under the causality constraint (when the propagation delay of the secondary path is greater than the primary path). A number of experimental results are presented in this paper to compare the performance of the FSLMS algorithm based virtual ANC algorithm with the FXLMS based virtual ANC algorithm.     

Adaptive variable step-size neural controller for nonlinear feedback active noise control systems

Adaptive filter techniques and the filtered-x least mean square (FxLMS) algorithm have been used in Active Noise Control (ANC) systems. However, their effectiveness may degrade due to the nonlinearities and modeling errors in the system. In this paper, a new feedback ANC system with an adaptive neural controller and variable step-size learning parameters (VSSP) is proposed to improve the performance. A nonlinear adaptive controller with the FxLMS algorithm is first designed to replace the traditional adaptive FIR filter; then, a variable step-size learning method is developed for online updating the controller parameters. The proposed control is implemented without any offline learning phase, while faster convergence and better noise elimination can be achieved. The main contribution is that we show how to analyze the stability of the proposed closed-loop ANC systems, and prove the convergence of the presented adaptations. Moreover, the computational complexities of different methods are compared. Comparative simulation results demonstrate the validity of the proposed methods for attenuating different noise sources transferred via nonlinear paths, and show the improved performance over classical methods.     

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

The FXLMS algorithm, which is extensively used in active noise control, exhibits frequency dependent convergence behavior. This leads to degraded performance for time-varying and multiple frequency signals. A new algorithm called the eigenvalue equalization filtered-x least mean squares (EE-FXLMS) has been developed to overcome this limitation without increasing the computational burden of the controller. The algorithm is easily implemented for either single or multichannel control. The magnitude coefficients of the secondary path transfer function estimate are altered while preserving the phase. For a reference signal that has the same magnitude at all frequencies, the secondary path estimate is given a flat response over frequency. For a reference signal that contains tonal components of unequal magnitudes, the magnitude coefficients of the secondary path are adjusted to be the inverse magnitude of the reference tones. Both modifications reduce the variation in the eigenvalues of the filtered-x autocorrelation matrix and lead to increased performance. Experimental results show that the EE-FXLMS algorithm provides 3.5-4.4 dB additional attenuation at the error sensor compared to normal FXLMS control. The EE-FXLMS algorithm's convergence rate at individual frequencies is faster and more uniform than the normal FXLMS algorithm with several second improvement being seen in some cases.     

Convex combination of nonlinear adaptive filters for active noise control

This paper proposes a nonlinear active noise control (ANC) system based on convex combination of a functional link artificial neural network (FLANN) and a Volterra filter. Simulation study reveals enhanced noise cancelation performance of the proposed ANC system over the ones based on its component filters.     

应用于声反馈抑制的变步长归一化子带自适应滤波算法*

针对自适应滤波算法中稳态失调量和收敛速度之间的矛盾,提出了一种新的变步长归一化子带自适应滤波算法。该算法在系统噪声抵消原理的基础上,用迭代收缩的方法估计得到无噪先验子带误差的功率,对每个子带步长进行更新。对所提出的算法进行数学分析,可以得出该算法是稳定的和收敛的。在长回声路径和短回声路径两种情况下,将该算法应用于助听器声反馈抑制系统中。相对于其他归一化子带自适应滤波算法,仿真实验表明,所提算法实现了更快的收敛速度,获得了更低的失调量。     

A simplified adaptive feedback active noise control system

In the adaptive feedback active noise control system based on the internal model control (IMC) structure, the reference signal is regenerated by synthesizing the error signal and the secondary signal filtered with the estimation of the secondary path, hence more computation load and extra programming are required. Motivated by the engineering truth that the primary noise cannot be completely cancelled in most practical active noise control applications and the error signal still contains some portions of the primary noise, a simplified adaptive feedback active noise control system is proposed in this paper, which adopts the error signal directly as the reference signal in an adaptive feedforward control system and utilizes the leaky filtered-x LMS algorithm to update the controller. The convergence properties of the proposed system are investigated and its advantages are discussed by comparing with other feedback control systems as well as the weakness. Finally, simulations and experiments are carried out to demonstrate the effectiveness of the proposed system.     

A robust adaptive hybrid feedback cancellation scheme for hearing aids in the presence of outliers

It has been demonstrated that the Filtered-x Wilcoxon LMS (FxWLMS) based adaptive filter mitigates the effect of the outliers acquired by the microphone signal of hearing aids by minimizing the Wilcoxon norm and hence shows better cancellation performance than the existing Filtered-x LMS (FxLMS) algorithm. The prediction error method based adaptive feedback canceller (PEMAFC) reduces the bias present in the estimate of the feedback path due to the continuous adaptive filtering (CAF). However, the impulse response of the measured feedback path is close to zero for the first many samples due to the delay introduced by ADC converters and then contains few significant values, which results in slow convergence rate when an adaptive filter is used to model the same. To overcome this limitation, we propose a proportionate normalized WLMS (PNWLMS) algorithm based PEMAFC (P-PNWLMS) for feedback cancellation in hearing aid in the presence of outliers. Further, with an objective to improve the convergence rate and performance accuracy simultaneously, this paper proposes a novel convex PNWLMS (CPNWLMS) algorithm which incorporates convex combination of PNWLMS and WLMS algorithms. The weight update equations are derived for PEMAFC trained by PNWLMS (P-PNWLMS) and CPNWLMS (P-CPNWLMS) algorithms respectively. The results of the simulation study show improved performance of the proposed CPNWLMS based adaptive filter over its component filters.     

一种基于虚拟传感的无需误差传声器的自适应有源降噪方法*

该文基于虚拟传感技术引入了一种用于耳机的无需误差传声器的自适应有源降噪方法。该算法仅使用一个参考传声器实现了一种前馈和反馈自适应算法结合的有源降噪算法,提高了有源降噪稳定性,简化了耳机硬件结构。利用DSP平台实现了该文提出的方案,并通过实验验证了其良好的降噪性能和实用价值。     

Robust active control of broadband noise in finite ducts

This study focuses on robust active control of broadband noise in finite ducts. Our analytical and experimental studies suggest the existence of several technical flaws in the path models of conventional active noise control (ANC) systems. These are sensitivity of the path model with respect to boundary conditions, and nonminimum phase (NMP) secondary and reference paths. For finite ducts with small cross sections, the traveling wave model (TWM) may be adopted to find an effective solution to these problems and lead to a robust ANC system. Since many practical "noisy" ducts are finite with small cross sections, the proposed ANC has many practical applications. Its robustness and ability to suppress broadband noise will be explained theoretically and verified experimentally.     

Fast affine projections and the regularized modified filtered-error algorithm in multichannel active noise control

In this paper, real-time results are given for broadband multichannel active noise control using the regularized modified filtered-error algorithm. As compared to the standard filtered-error algorithm, the improved convergence rate and stability of the algorithm are obtained by using an inner-outer factorization of the transfer path between the actuators and the error sensors, combined with a delay compensation technique using double control filters and a regularization technique that preserves the factorization properties. The latter techniques allow the use of relatively simple and efficient adaptation schemes in which filtering of the reference signals is unnecessary. Results are given for a multichannel adaptive feedback implementation based on the internal model control principle. In feedforward systems based on this algorithm, colored reference signals may lead to reduced convergence rates. An adaptive extension based on the use of affine projections is presented, for which real-time results and simulations are given, showing the improved convergence rates of the regularized modified filtered-error algorithm for colored reference signals.     

多通道FxAP算法的电动汽车路噪控制

汽车噪声控制是主动噪声控制领域中经典的问题.伴随着电动化的普及,路噪控制将取代内燃机噪声控制,逐渐成为汽车噪声控制的主要领域.针对传统车内路噪控制系统适应性差、算法收敛速度慢、降噪量不足的问题,该文使用了多通道滤波-x仿射投影(FxAP)算法加快收敛速度,从而实现对噪声的快速追踪并控制.通过搭建了车内多通道头靠噪声控制...     

Simulations and experiments for hybrid noise control systems

The purpose of this study is to explore the effects of sound elimination in a cylindrical duct by combining a reactive muffler and active noise control (ANC) system. Besides the exploration via experiment of the combined noise control system, a Grey prediction based on Grey theory is also applied to ANC for this hybrid system.In the experiment for this system, a combined adaptive algorithm is adopted. The results of sound elimination are compared between cases with ANC systems installed before the muffler and after the muffler. The results indicate that the sequence of arrangement of muffler can influence the results of active noise control. According to the results of experiment and simulation, the effect of noise reduction in ANC system is influenced extremely by reference signal received. The transmission loss and insertion loss in this system are also discussed in details. Besides, the experimental results indicate that the hybrid system has the advantages over a traditional muffler when the muffler is not designed for the frequency of the noise. Furthermore, the mathematic simulation for acoustic field in a cylindrical duct with a muffler is performed in order to verify the experiment results. Finally, Grey theory is applied to estimate the expected signals in order to perform a computer simulation of Grey prediction to explore effects of the ANC system. The results indicate that application of Grey theory gives a good control for the hybrid system.