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.     

Binaural active noise control using parametric array loudspeakers

This paper reports the binaural active noise control (ANC) system developed to deal with factory noise. The control points are located in the vicinity of the left and right ears of a worker sitting along the production line. Due to the complicated safety requirements in the factory, secondary sources and error microphones are not allowed to be placed near the worker. Therefore, the proposed ANC system employs the feedforward structure and adopts the parametric array loudspeakers (PALs) as the secondary sources. The PAL is a type of directional loudspeaker that generates a much narrower sound field as compared to the conventional loudspeaker. Once the proposed ANC system has been trained offline, the error microphones can be removed. The performance of the binaural ANC system is successfully demonstrated based on a digital signal processor (DSP) implementation.     

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.     

Active noise control in a duct by an analog neural network circuit

Conventional active noise control (ANC) in ducts has been realized with digital signal processing. The physical size of the conventional ANC systems is usually large owing to the signal processing interval, and the cost of the system depends on the price of the digital signal processor (DSP). This paper proposes a new ANC system with an analog neural network circuit, which will process signals in short time periods without DSP. The proposed neural network circuit has a simple structure consisting of analog multipliers and an integrator, and we simulated the performance of the circuit by HSPICE. We also fabricated a circuit connected to a real duct and confirmed operation of the proposed ANC system.     

Causality study on a feedforward active noise control headset with different noise coming directions in free field

A systematic analysis is proposed to predict the performance of a typical feedforward single channel ANC headset in terms of the delay, especially the non-causal delay caused by different noise coming directions. First, the performance of a non-causal feedforward system for a band-limited noise is analyzed by using a simplified pure delay model, where it is found that the noise reduction bandwidth is narrowed and the maximum noise reduction is decreased with the increase of the non-causal delay. Second, a systematic method is developed, which can be used to predict the system performance with measured primary and secondary path transfer functions in most practical sound fields and to study the effects of the control filter length and the path delay on the performance. Then, the causality of a typical feedforward active noise control headset with the primary source at 0° and 90° positions in an anechoic chamber is analyzed, and the performance for the two locations predicted by the systematic analysis is shown in good agreements with the experiment results. Finally, an experiment of a typical feedforward active noise control headset in a reverberation chamber is carried out, which shows the validity of the proposed systematic analysis for other more practical sound fields.     

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.     

一种用于主动降噪耳机的权重滤波误差信号滤波-x最小均方算法*

针对传统FxLMS算法前馈自适应主动降噪耳机系统因果性条件不足时在宽带噪声环境中产生的高频噪声抬升问题,该文引入权重滤波误差信号FxLMS算法用于抑制高频噪声的抬升,但该算法带来了低频降噪量不足问题。因此,进一步提出将固定系数混合控制器与权重滤波误差信号FxLMS算法结合,在解决高频噪声抬升问题的同时,保证了良好的低频降噪量。基于DSP平台实现了提出的主动降噪耳机方案。实验证明,该方案针对宽带和单频等噪声都取得了较好的降噪效果。     

IMPLEMENTATION OF A BROADBAND DUCT ANC SYSTEM USING ADAPTIVE SPATIALLY FEEDFORWARD STRUCTURE

An adaptive spatially feedforward algorithm is proposed for broadband attenuation of noise in ducts. Acoustic feedback generally exists in this active noise control structure. Munjal and Eriksson (1988 Journal of Acoustical Society of America84, 1086-1093) derived an ideal controller for the spatially feedforward structure. The ideal controller can be partitioned into two parts. The first part represents a repetitive controller that can be implemented by an infinite impulse response (IIR) filter, whereas the second part represents the dynamics of transducer that can be implemented by a finite impulse response (FIR) filter. In the paper, the IIR filter is merged with the original plant. The FIR filter is adaptively updated by the least-mean-square (LMS) algorithm to accommodate perturbations and uncertainties in the system. The proposed algorithm is implemented via a floating point digital signal processor and compared with other commonly used algorithms such as the Filtered-X LMS algorithm, the feedback neutralization algorithm, and the Filtered-U LMS algorithm. Experimental results show that the system has attained 15·7 dB maximal attenuation in the frequency band 200-600 Hz.     

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.     

FEEDFORWARD ALGORITHMS WITH SIMPLIFIED PLANT MODEL FOR ACTIVE NOISE CONTROL

Most feedforward active noise control (ANC) algorithms require models of electro-acoustic paths. To obtain satisfactory attenuation and keep the system stable these models have to represent the plant well. This, according to the literature, requires estimation of many, often hundreds of coefficients. Then, control filters also have very large, comparable structures. Such an approach reveals significant drawbacks if paths of the plant are subject to change. Estimation of so many plant models and control filter coefficients is very slow and time consuming. Therefore, the speed of adaptation is substantially reduced. This can be accepted in some unmoveable plants like acoustic ducts. However, there are many other plants, e.g., active personal hearing protection devices, in which rapid reaction is also of utmost interest not to annoy the user. In this paper, an alternative approach is proposed that does not need precise models except an estimate of the discrete time delay of the plant. However, according to the literature this leads to a relatively narrow attenuation band, which is confirmed for classical control structures like finite and infinite impulse response filters. This becomes a premise to design a new control algorithm. First, the so-called phase shifters (in two versions) are designed. They enable to control narrowband noise on comparable levels with at least an order less parameters than the filters mentioned above. To control broadband noise, the idea of phase shifter banks is then put forward. In turn, to extend the attenuation band conversion of sampling frequency is adopted to noise control problems. Finally, the algorithm combining advantages of phase shifter banks and conversion of sampling frequency allows controlling of any noise over any frequency band, with limits imposed only by the signal processor available and pass-band of the secondary source. Although this algorithm is designed generally and can be applied to any ANC plant, for laboratory experiments an active personal hearing protection device is used.     

Improving robustness of active noise control in ducts

A robust active noise controller (ANC) is proposed here for finite ducts. While the H(infinity) control theory provides theoretical ground and numerical algorithms to design robust controllers, it is important for an engineer to design and formulate a robust controller so that the objective is more achievable and the H(infinity) constraints less restrictive without sacrificing robustness. A new robust ANC is designed this way with an extra actuator to improve achievable performance and introduce more degrees of freedom to controller parameters. The new strategy relaxes H(infinity) constraints without sacrificing robustness and enables the ANC to tolerate a wide variety of errors and uncertainties including truncation errors between a finite model and an infinite field. Theoretical analysis, numerical examples, and experimental results are presented to demonstrate the improved performance of the proposed ANC when subject to a certain level of uncertainties in a duct.     

参量阵扬声器在管道噪声控制中的研究*

为了解决管道有源噪声控制中声反馈造成的系统复杂度和计算量的增加,文中引入参量阵扬声器作为次级声源,利用其强指向性减小控制系统的声反馈。为了验证该方法可行性,本文分别在直管和L管中,对600 Hz单频噪声和频率范围为500 Hz~1000 Hz的窄带噪声进行了管道有源噪声控制,同时测量了参量阵扬声器的管内声场和降噪范围。结果表明,参量阵扬声器声反馈小,在没有声反馈补偿的条件下对单频噪声的降噪效果基本达到了声反馈补偿条件下普通扬声器的降噪效果,对窄带噪声的降噪效果稍差。此外,通过测量管道声场和降噪量,确定了参量阵扬声器的降噪区域为误差传感器下游整个管道,降噪面积为管道整个截面。这说明参量阵扬声器作为次级声源降低了系统的复杂度和算法的计算量,并取得了较好的降噪效果。     

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.     

Comparison of convergence characteristics of adaptive IIR and FIR filters for active noise control in a duct

There are perceived drawbacks to using adaptive IIR filters, as opposed to adaptive FIR filters, for active noise control (ANC). These include stability issues, the possible convergence of estimated parameters to biased and/or local minimum solutions and relatively slow rate of convergence. Stability issues can generally be resolved easily using well-established methods. In this Technical Note convergence rates are compared with particular reference to the active control of noise in a duct, for which the dynamics of the cancellation path are important. The characteristics of this application of ANC set it apart from usual signal processing applications of adaptive IIR filters and this has implications for the convergence properties. Various control approaches are considered: IIR least mean squares (IIR-LMS), IIR recursive least squares (IIR-RLS) with FASPIS (Fast Algorithm Secondary Path Integration Scheme) and FIR-LMS. Numerical examples are presented. It is seen that the cancellation path dynamics generally have the effect of changing the performance surface of the estimated IIR filter from bimodal to unimodal, which has consequences for improving the convergence rate of adaptive IIR filters. It is also seen that IIR-RLS has a comparable rate of convergence to FIR-LMS, with the steady-state performance being as good or better.     

A hybrid active noise controller for finite ducts

A hybrid active noise controller (ANC) is proposed to solve some existing problems, which are related to the non-minimum phase (NMP) path models between uncollocated sensors and actuators in many ANC systems. For hybrid ANC schemes, the NMP path causes design difficulties to both feedforward and feedback control. These problems can be solved effectively by adding an extra actuator in the ANC system. A new design procedure is presented to take the greatest advantage of the extra actuator. Theoretical analysis and experimental results are presented to show the improved performance of the proposed ANC.     

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.     

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.     

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.     

一种数字有源降噪耳机控制器设计方法

为了得到一种作用于低频宽带噪声的有源降噪耳机,采用固定系数的数字控制器实施降噪,并提出了一种前反馈混合的控制器设计方法。比较了前馈及混合两种控制模式下对低频宽带噪声的控制效果;进一步提出了一种综合优化方法,改善噪声不同角度入射下的降噪性能。仿真和基于DSP平台的实验表明,提出的方法对多方向入射的20～1500 Hz低频宽带噪声均具有较好控制效果。     

基于脉冲声分离的刚性球散射声控制

提出了一种基于脉冲声的三维空间中刚性球散射声分离方法,并利用前馈、固定系数控制方式对分离出的散射声进行有源控制,抑制散射声强度,实现了刚性球散射体在观测点处“声学不可见”。该方法利用脉冲信号作为初级噪声,通过有无刚性球时传声器采集脉冲信号的差值确定散射声大小,实现散射声与声源直达声的分离。对分离出的散射声进行多通道有源控制以验证该文所提分离方法及控制系统的有效性。实验结果表明,700~1000 Hz范围内,有源控制开启后,双通道散射声的平均降噪量大于5 dB,多通道散射声的平均降噪量大于8 dB,且误差传声器处采集的残余声场与无刚性球时采集的初级声场信号波形基本一致,实现了刚性球散射体在误差传声器处“声学不可见”。此外,参考传声器布放位置的选取问题也在该文做了详细讨论。