Broadband Active Noise Control Research Articles

A semi-adaptive feedforward hybrid active noise control algorithm for multichannel systems.

Broadband active noise control systems incorporating fixed controllers exhibit limited ability to reduce sinusoids. This study presents a semi-adaptive feedforward hybrid active noise control (HANC) system to address this issue. The proposed system pairs fixed high-order optimal controllers for broadband noise with adaptive low-order FXLMS-based controllers for narrowband noise. Notably, parallel broadband and narrowband controllers work independently. The proposed semi-adaptive feedforward HANC system demonstrates low computational complexity which makes it suitable for multichannel systems. Simulations and experiments validate the effectiveness of the proposed system in controlling mixed noise.

A survey on filtered-x least mean square-based active noise control systems with emphasis on reducing computational complexity

Active noise control (ANC) is gaining ever-increasing attention owing to its powerful ability to attenuate low-frequency noise. The computational complexity of an ANC system may directly affect its computational efficiency, control performance, and hardware costs. Therefore, the focus of this paper is mainly on discussing the development of ANC systems with emphasis on reducing computational complexity. The ANC systems are classified into two groups of narrowband and broadband systems. The computational complexity analysis is provided to show the computational merit of each system with respect to the conventional ANC systems. In addition, numerical simulations are performed to evaluate the convergence speed and noise reduction performance of the considered systems. The results show that, in the narrowband ANC systems, the LFE-NANC, CFX-NANC and BFX-NANC systems enjoy better overall performance in terms of the computational complexity, convergence speed and steady-state error, and in the broadband ANC systems, the DF-BANC system has the lowest computational complexity but cannot effectively attenuate the broadband noise with high spectral dynamics, whereas the DS-BANC and MDS-BANC systems can. This study provides in-depth insight into current typical low-complexity ANC systems.

Wavelet packet transform applied to active noise control system for mixed noise in nonlinear environment

The noise emitted from rotating machinery usually presents a mixture of broadband and narrowband frequency components. Hybrid functional link artificial neural network (HFLANN) system consisting of narrowband ANC (NANC) subsystem, broadband ANC (BANC) subsystem and sinusoidal noise canceller (SNC) subsystem is effective to suppress the mixed noise. However, in the conventional HFLANN system, the attenuation performance of broadband subsystem cannot meet the requirement, the narrowband subsystem cannot adapt to the nonlinear environment. To address the problems, an improved HFLANN (IHFLANN) system is proposed in this paper. By applying the wavelet packet (WP) structure, the broadband noise is decomposed into different frequency bands, which improves the attenuation performance of broadband subsystem. The FLANN structure is applied to the NANC subsystem to improve the steady-state performance in nonlinear environment. Meanwhile, to reduce the computational complexity, we introduce a simplified IHFLANN (SIHFLANN) system. Simulation results demonstrate the proposed systems achieve better attenuation performance and the simplified system reduces computational complexity without sacrificing the attenuation performance.

Robust feedback controller combined with the remote microphone method for broadband active noise control in headrest

This paper proposes a design method combining the remote microphone method (RMM) with a robust fixed feedback controller to achieve active noise control in a headrest with physical microphones situated far from the target zone. Design objectives of the controller are based on a mixed H2/H∞ method and the proposed closed-loop gain margin constraint, which consider noise reduction performance, waterbed lift, and robustness against plant perturbations due to slight rotations of the head. Meanwhile, the design objectives are constructed with RMM to create a local zone of quiet far away from the physical monitoring microphone. Particle swarm optimization algorithm is employed for this multi-objective design problem to efficiently generate the feedback controller consisting of cascade second-order sections infinite-impulse-response (IIR) filters. Simulations and real-time experiments were conducted to demonstrate the superior noise reduction performance and robust stability of the designed IIR feedback controller in attenuating broadband disturbances measured in a vehicle.

Optimal parametric design of delayless subband active noise control system based on genetic algorithm optimization

Active noise control systems are generally application-specific, and an appropriate algorithm with an optimal configuration is desirable in the first stage of active noise control system design and deployment. This study presents a design of the subband active noise control system with optimal parameters for a practical broadband active noise control. Although the delayless subband active noise control has gained wide attention for broadband noise cancellation, an optimal design remains a challenge because of the complex interplay between multiple factors such as spectral leakage, delay and weight stacking distortion subject to a number of configurable parameters, and weight stacking method. The configurable parameters can hardly be optimized independently because the active noise control performance depends on the combined configuration. A simple near black box active noise control algorithm optimization model is thus established by incorporating the genetic algorithm optimization into the parametric design of the delayless subband algorithm. The automated process does not require an understanding of the performance characteristics for different parameters. The significance of applying the automated genetic algorithm optimization to the complex multiparameter nonlinear active noise control design is revealed by numerical simulations, particularly for the multichannel low-frequency broadband active noise control system configured with the delayless subband algorithms. This provides a way for the optimal parametric design of subband active noise control before being used in a practical complex scenario.

A Subband Adaptive Filtering for Distributed Active Noise Control Systems

This study proposes an extension of the subband adaptive filtering technique to distributed active noise control systems and the details of the algorithm are presented. The computational requirements and convergence performance are examined for a network with a ring topology without constraints in communication. The proposed algorithm divides the signal of each node into several subbands to reduce the dynamic range of the spectrum and consequently accelerate the convergence speed. Since the subband decomposition contains a decimation process, the computational complexity is reduced as the number of subbands is increased. Simulations are conducted to compare different algorithms and an 8‐node network is studied in terms of noise reduction performance. The results demonstrate the efficacy of the proposed algorithm for broadband active noise control and the convergence speed could be improved compared to the distributed multiple error filtered‐x (DMEFxLMS) algorithm. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A modified feedforward hybrid active noise control system for vehicle

The feedforward hybrid active noise control (HANC) system combines the strengths of the narrowband ANC (NANC) system and the broadband ANC (BANC) system. Taking this advantage into account, this paper applies it to attenuate the vehicle interior noise mixed with narrowband and broadband components. However, in the HANC system, the NANC subsystem and BANC subsystem are fed a common error signal which depends on the combined secondary signals from the both subsystems. This causes the problem of mutual coupling and hence affects the noise reduction performance. To tackle the problem, we propose a modified HANC (MHANC) system in this paper. In the MHANC system, the error signal of each ANC subsystem is independently synthesized on the basis of the estimated primary and secondary signals. Note that the NANC system for engine order noise control suffers performance deterioration when the fluctuating real-time engine speed signal is used for constructing internal reference signals. For performance improvement, an enhanced NANC (ENANC) system is developed by smoothing the fluctuating engine speed signal. Meanwhile,the ENANC system is incorporated in the MHANC system to form an enhanced MHANC (EMHANC) system. Simulations were performed on the vehicle interior noise recorded under actual driving conditions. The corresponding results demonstrate the superiority of the proposed MHANC and EMHANC systems.

Model decomposition via optical delay estimation using the camera tracking in an active noise control system for creation of a movable quiet zone

This article presents an adaptive control system for active local reduction of broadband noise at moving locations, using the camera tracking for path model decomposition to reduce the filter lengths. To enable a dynamic placement of local quiet zones with respect to a moving target, previous works proposed the combina- tion of the remote microphone technique with a camera-based target tracking. The estimated 3-D coordinates are used at run time for a dynamic update of the trans- fer paths models, which correspond to virtual microphones at predetermined loca- tions. Nevertheless, whereas current applications like headrests feature only short distances to the target, the considered ANC system aims at larger ranges for the moving quiet zone, resulting in long impulse responses and high delays in the transfer paths. To reduce the associated model lengths, this work evaluates a decomposed identification stage that takes advantage of the camera-tracking sys- tem by estimating the acoustic path delays optically. In experiments, this method is shown to be superior to signal processing-based approaches like cross-correlation and thus enables an accurate separation of the delays. Eventually, the valida- tion of the broadband ANC performance at a moving microphone shows that the quiet zone could be tracked over a range of 0.8 m, while using only few transfer path models and saving over 100 coefficients due to the proposed decomposition.

A Fuzzy Logic-Based Gain Scheduling Method for Online Feedback Path Modeling and Neutralization in Active Noise Control Systems

Acoustic feedback is the main problem associated with (broadband) active noise control (ANC) in feed-forward configuration. To solve this problem, auxiliary noise is injected into the ANC system to have accurate model of the feedback path. The conventional approaches substantially model the feedback path at the cost of degradation in the noise reduction performance (NRP) and vice versa. Here, we propose a fuzzy logic-based gain scheduling (of auxiliary noise) for online feedback path modeling and neutralization (FBPMN). The fuzzy controller computes the instantaneous gain for auxiliary noise based on two inputs, the first input gives information about modeling status of FBPMN filter while the second input gives information regarding variance of the disturbance signal for the adaptive FBPMN filter. Furthermore, variable step-size (VSS) is used for the adaptation of FBPMN filter that uses a larger value of step-size during modeling (phase) of FBPMN filter for fast adaptation and a smaller value when the feedback path has been (adequately) modeled. Fuzzy gain scheduler together with VSS in FBPMN filter improves both the NRP and feedback path modeling characteristics. Moreover, the proposed method does not require initial offline modeling of the feedback path thereby demonstrating complete online operation. To make the system computationally efficient, a look-up table-based approach is also proposed in this paper. Simulations results are presented to demonstrate the effectiveness of the proposed method.

Frequency-Domain Filtered-x LMS Algorithms for Active Noise Control: A Review and New Insights

This paper presents a comprehensive overview of the frequency-domain filtered-x least mean-square (FxLMS) algorithms for active noise control (ANC). The direct use of frequency-domain adaptive filters for ANC results in two kinds of delays, i.e., delay in the signal path and delay in the weight adaptation. The effects of the two kinds of delays on the convergence behavior and stability of the adaptive algorithms are analyzed in this paper. The first delay can violate the so-called causality constraint, which is a major concern for broadband ANC, and the second delay can reduce the upper bound of the step size. The modified filter-x scheme has been employed to remove the delay in the weight adaptation, and several delayless filtering approaches have been presented to remove the delay in the signal path. However, state-of-the-art frequency-domain FxLMS algorithms only remove one kind of delay, and some of these algorithms have a very high peak complexity and hence are impractical for real-time systems. This paper thus proposes a new delayless frequency-domain ANC algorithm that completely removes the two kinds of delays and has a low complexity. The performance advantages and limitations of each algorithm are discussed based on an extensive evaluation, and the complexities are evaluated in terms of both the peak and average complexities.

A New Online Secondary Path Modeling Method with An Auxiliary Noise Power Scheduling Strategy for Narrowband Active Noise Control Systems

In recent years, the online secondary path modeling (SPM) method with an auxiliary noise power scheduling strategy has been crucial for active noise control (ANC) systems and has also become a popular research topic. However, most scheduling strategies have been designed for broadband active noise control (BANC), and these ideas may not be directly applied to narrowband active noise control (NANC) systems due to the difference in structure between BANC and NANC systems. In this paper, a new online SPM method with auxiliary noise power scheduling is proposed. Here, the controlled system is adapted using the filtered-x weighted accumulated least mean square (FXWALMS) algorithm proposed by the authors. Moreover, the auxiliary noise power is scheduled based on the convergence status of the forgetting factor to accurately track the change in the NANC system. As a result, the proposed method not only achieves good modeling accuracy and fast convergence but also considerably increases noise attenuation. Extensive simulations are conducted to prove the superior performance of the proposed method in various scenarios.

A numerically stable, finite memory, fast array recursive least squares filter for broadband active noise control

SummaryFor broadband active noise control applications with a rapidly changing primary path, it is desirable to find algorithms with a rapid convergence, a fast tracking performance, and a low computational cost. Recently, a promising algorithm has been presented, called the fast‐array Kalman filter, which uses rotation matrices to calculate the filter parameters. However, when this algorithm is implemented, it can show unstable behavior because of finite precision error propagation. In this paper, a novel algorithm is presented, which exhibits the fast convergence and tracking properties and the linear calculation complexity of the fast‐array Kalman filter but does not suffer from the mentioned numerical problems. This is accomplished by running two finite length growing memory recursive least squares filters in parallel and using a convex combination of the two filters when the control signal is calculated. A reset of the filter parameters with proper re‐initialization is enforced periodically. The mixing parameters will be chosen in such a way that the total available information used for the calculation of the control signal will be approximately equal at every time instance. The performance of the filter is shown in numerical simulations and real‐time lab experiments. The numerical experiments show that the algorithm performs better numerically than the fast‐array sliding window recursive least squares filter, while achieving a comparable convergence rate and tracking performance. The real‐time lab experiments confirm the behavior shown in the simulations. Copyright © 2015 John Wiley & Sons, Ltd.

Reply to “Comments on ‘A New Feedforward Hybrid Active Noise Control System’”

In this reply, we first provide a MATLAB program used in our simulations and clarify our claim regarding the occurrence of the so-called “firework” noise in the broadband active noise control (BANC) system. Next, we present some simulation results of the BANC using the FXLMS and the normalized FXLMS (NFXLMS) algorithms in the presence of a real noise signal generated by a large-scale rotating machine. The real noise is a mixture of several low-frequency sinusoids and a wideband noise component. The existence of “firework” noise is again confirmed in the BANC system when it is made to converge relatively fast.

Comments on "A New Feedforward Hybrid ANC System" - An addendum

The authors of the original article [ibid, vol. 18, no. 10, pp. 591-594, 2011] have submitted the Matlab code they used in their simulations. In their reply they insist that the traditional, broadband ANC system "may become awkward and its performance 'may degrade' seriously when the reference and primary noise signals contain both low-frequency sinusoid and wideband noise component and its convergence is made relatively fast." The "awkwardness" is expressed by the existence of the "firework" noise. In this comment the author does not question the possibility of the "firework" noise to appear in the output signal. He provides a proof that the reason the original authors give for the "fireworks" is wrong, and that the performance degradation was to be expected.

Comments on “A New Feedforward Hybrid ANC System”

This correspondence shows that some statements from the letter in the title, which are given without any theoretical analysis, are in conflict with the literature on active noise control systems. This correspondence also shows that the traditional, broadband ANC systems deal well with a mixture of broadband and narrowband noise.

Multi-channel Kalman filters for active noise control

By formulating the feed-forward broadband active noise control problem as a state estimation problem it is possible to achieve a faster rate of convergence than the filtered reference least mean squares algorithm and possibly also a better tracking performance. A multiple input/multiple output Kalman algorithm is derived to perform this state estimation. To make the algorithm more suitable for real-time applications, the Kalman filter is written in a fast array form and the secondary path state matrices are implemented in output normal form. The resulting filter implementation is tested in simulations and in real-time experiments. It was found that for a constant primary path the filter has a fast rate of convergence and is able to track changes in the frequency spectrum. For a forgetting factor equal to unity the system is robust but the filter is unable to track rapid changes in the primary path. A forgetting factor lower than 1 gives a significantly improved tracking performance but leads to a numerical instability for the fast array form of the algorithm.

A robust hybrid active noise control system using IIR notch filters

Noise signals generated by rotating machines usually contain both wideband and sinusoidal components. The conventional broadband active noise control (BANC) is generally effective for reducing such noise signals, but its performance may degenerate significantly when the frequencies of the sinusoids are very small. The narrowband ANC (NANC) is good at dealing with the sinusoidal component, but it is powerless with the wideband noise. A hybrid ANC (HANC) has been proposed recently to suppress both components simultaneously. However, it is vulnerable in the presence of sensor error. In this paper, we propose a new structure for the HANC that presents very nice robustness to sensor error. The proposed HANC uses a bandpass filter bank whose elements are derived from IIR notch filters with constrained poles and zeros, and is capable of mitigating the frequency mismatch (FM) due to the non-acoustical sensor fatigue, aging, etc. Extensive simulations are provided to prove the performance advantages of the proposed system.

Performance Analysis and Design of FxLMS Algorithm in Broadband ANC System With Online Secondary-Path Modeling

The filtered-x LMS (FxLMS) algorithm has been widely used in active noise control (ANC) systems, where the secondary path is usually estimated online by injecting auxiliary noises. In such an ANC system, the ANC controller and the secondary-path estimator are coupled with each other, which make it difficult to analyze the performance of the entire system. Therefore, a comprehensive performance analysis of broadband ANC systems is not available currently to our best knowledge. In this paper, the convergence behavior of the FxLMS algorithm in broadband ANC systems with online secondary-path modeling is studied. Difference equations which describe the mean and mean square convergence behaviors of the adaptive algorithms are derived. Using these difference equations, the stability of the system is analyzed. Finally, the coupled equations at the steady state are solved to obtain the steady-state excess mean square errors (EMSEs) for the ANC controller and the secondary-path estimator. Computer simulations are conducted to verify the agreement between the simulated and theoretically predicted results. Moreover, using the proposed theoretical analysis, a systematic and simple design procedure for ANC systems is proposed. The usefulness of the theoretical results and design procedure is demonstrated by means of a design example.

A New Feedforward Hybrid Active Noise Control System

Performance of the conventional broadband active noise control (ANC) system may degrade severely if its primary and reference noise signals contain both wideband and narrowband components simultaneously. In this letter, we propose a new feedforward hybrid ANC system capable of reducing such primary noise signals. First, typical simulation results are provided to show the performance deterioration of the conventional system in the presence of mixture of wideband and narrowband components. Next, a new hybrid ANC system is proposed to tackle the problem. The new system consists of three subsystems, i.e., a sinusoidal noise canceller, a broadband and a narrowband ANC subsystem, which work in harmony. Extensive simulations are conducted to demonstrate the effectiveness of the proposed system.

Combined MIMO adaptive and decentralized controllers for broadband active noise and vibration control

Model errors in multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. In this paper, a combination of high-authority control (HAC) and low-authority control (LAC) is considered for improved performance in case of such model errors. A digital implementation of a control system is presented in which the HAC (adaptive MIMO control) is implemented on a CPU and in which the LAC (decentralized control) is implemented on a high-speed Field Programmable Gate Array. Experimental results are given which demonstrate that the HAC/LAC combination leads to performance advantages in terms of stabilization under parametric uncertainties and reduction of the error signal.