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.     

Improving robustness of filtered-x least mean p-power algorithm for active attenuation of standard symmetric-α-stable impulsive noise

The paper concerns active control of impulsive noise having peaky distribution with heavy tail. Such impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The most famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems is based on the minimization of variance (second order moment) of error signal, and hence, becomes unstable for the impulsive noise. In order to improve the robustness of adaptive algorithms for processes having distributions with heavy tails (i.e. signals with outliers), either (1) a robust optimization criterion may be used to derive the adaptive algorithm or (2) the large amplitude samples may be ignored or replaced by an appropriate threshold value. Among the existing algorithms for ANC of impulsive noise, one is based on the minimizing least mean p-power (LMP) of the error signal, resulting in FxLMP algorithm (approach 1). The other is based on modifying; on the basis of statistical properties; the reference signal in the update equation of the FxLMS algorithm (approach 2). In this paper we propose two solutions to improve the robustness of the FxLMP algorithm. In first proposed algorithm, the reference and the error signals are thresholded before being used in the update equation of FxLMP algorithm. As another solution to improve the performance of FxLMP algorithm, a modified normalized step size is proposed. The computer simulations are carried out, which demonstrate the effectiveness of the proposed algorithms.     

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.     

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.     

Dynamic Active Noise Control of Broadband Noise in Fighter Aircraft Pilot Helmet

This paper presents the development of a dynamic Active Noise Control (ANC) algorithm aimed towards reducing the broadband noise inside the helmet earcups of a fighter aircraft pilot helmet. The dynamic ANC involves a Variable Step-Size Griffiths (VSSG) FxLMS algorithm to attenuate noise entering directly through helmet, a LMS based adaptive noise canceller to attenuate noise entering through the pilot microphone, and energy detectors for failure protection and optimized battery power usage. The algorithms are implemented on Texas Instruments’ TMS320C6748 processor and are tested in a helmet ANC experimental setup.     

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。     

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.     

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.     

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.     

Simulation study on active noise control for a 4-T MRI scanner

The purpose of this work is to study computationally the possibility of the application of a hybrid active noise control technique for magnetic resonance imaging (MRI) acoustic noise reduction. A hybrid control system combined with both feedforward and feedback loops embedded is proposed for potential application on active MRI noise reduction. A set of computational simulation studies were performed. Sets of MRI acoustic noise emissions measured at the patient's left ear location were recorded and used in the simulation study. By comparing three different control systems, namely, the feedback, the feedforward and the hybrid control, our results revealed that the hybrid control system is the most effective. The hybrid control system achieved approximately a 20-dB reduction at the principal frequency component. We concluded that the proposed hybrid active control scheme could have a potential application for MRI scanner noise reduction.     

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。     

基于幅度相位联合校正算法的8-QAM自由空间相干光通信

提出了基于幅度相位联合校正算法的8阶正交幅度调制(8-QAM)自由空间相干光通信方案。与传统的自由空间光通信方案相比,本文提出的方案不仅无需信道状态信息(CSI)就可以实现对原信号的高精度还原,同时还具有较高的光谱效率。仿真实验表明,当接收端与发射端的频偏f 0=20 MHz、激光器联合线宽Δf=10 kHz、信噪比为20 dB时,该方案在归一化大气闪烁标准差σ=0.25、归一化相位噪声方差σΦ^2=0.07的对数正态湍流信道条件下,其误码率(BER)与未采用联合校正算法的8-QAM系统相比低4个量级。     

Design and experimental tests of active control barriers for low-frequency stationary noise reduction in urban outdoor environment

Active noise control (ANC) techniques are based on the emission of an antiphase signal in order to cancel the noise produced by a primary source. ANC has been successfully applied especially for reducing noise in confined environments, such as headphones and ducts. In this study, we present an application of ANC concepts to the design of an anti-noise barrier for an outdoor environment and its experimental testing. Even though passive techniques are effective in noise reduction at middle-high frequencies, they become less efficient at low frequencies (below 300 Hz) due to the limited dimensions of commonly deployable barriers. In this paper, we analyze the properties of a low-cost active noise system able to efficiently operate on stationary, almost pure-tone, low-frequency noise, such as that produced by electrical transformers and reactors in power and transformation plants. A prototype has been implemented and on-the-field experimental tests have been carried out. The results (confirmed also by numerical simulations) demonstrate a remarkable efficiency in the far field, with a reduction up to 15 dB with respect to the absence of the ANC system.     

基于相位调制-解调的光纤激光相位噪声检测方法研究

在主动相位控制相干合成中,常用的光纤激光主动相位控制方法主要有外差法、多抖动法和随机并行梯度下降算法等. 基于多抖动法和外差法的原理,提出了一种新型的基于相位调制-解调的相位检测与控制方法. 该方法利用周期信号对参考光进行相位调制,将调制后的参考光与待检测信号光进行相干检测,通过对相干光强信号和相位调制信号的融合处理,实现相位噪声的检测和控制. 对该方法进行了数值模拟和实验研究. 实验结果表明,对于频率为2 kHz,噪声范围为[0,2π)的正弦噪声,相位检测精度优于λ/50,控制精度可达 关键词： 光纤激光 相干合成 相位噪声检测 调制-解调     

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。     

调节水床效应的双梯度有源噪声控制自适应算法*

为了使自适应反馈有源噪声控制系统能够兼顾水床效应,通过约束次级信号的能量以调节噪声放大,设计了一种双梯度算法。当次级信号满足约束,算法沿着最小化误差信号能量的梯度方向迭代,反之,则沿着最小化次级信号能量的方向迭代。在有源降噪耳机实例中的对比结果表明,该算法能调节噪声放大并保持较大的降噪带宽,且运算量没有显著增加。     

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.     

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.     

Novel iteration-free blind phase noise estimation for coherent optical OFDM

We propose a novel iteration-free blind phase noise estimation scheme for coherent optical orthogonal frequency division multiplexing （CO-OFDM） systems. In the new algorithm, the cost function is selected as the similar expression with real and imaginary parts as that in the modified constant modulus algorithm, and the new cost function is derived under some assumptions, where it is infinitely approximated by the sine and cosine functions. By means of the analytical formula of the cost function, the initial coarse common phase error can be obtained with only some samples, where the algorithm avoids computational complexity of conventional blind phase noise compensation scheme. In CO-OFDM systems with high-order modulation format （32 quadrature amplitude modulation） and narrow linewidth lasers, it is proved by the simulation results that the nhase noise can be effectively compensated with the proposed blind estimation method.     

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.