A design of an adaptive active noise control system in driver's cab

Accurate model of secondary paths is very crucial for the multi-channel filtered-X least mean square algorithm applied in adaptive active noise control system. The auxiliary random noise technique is popular for online secondary path modeling during adaptive active noise control operation. This paper proposes a simplified variable step-size strategy and an effective auxiliary noise power scheduling strategy for the multi-channel filtered-X least mean square algorithm. Through a defined indirect error signal, the proposed method can guarantee every online secondary path modeling filter has its own exclusive variable step-size strategy to update their coefficients, and every injected noise has its own exclusive scheduling strategy considering all of the corresponding online secondary path modeling filters. The proposed method can improve the adaptive performance and simplifies the complexity of multi-channel adaptive active noise control system. Computer simulations show that the proposed method gives much better noise reduction and secondary path modeling accuracy at a somewhat faster convergence rate comparing with the competing methods.

Integrated active noise control for open-fit hearing aids with customized filter

In this paper properties of adaptive algorithms utilising ideas of stochastic gradient search optimisation applied to noise reduction are discussed. A focus on their average rate of convergence as well as on the obtained noise reduction is given. The presented discussion is based on a simulation case study devoted to noise reduction using a feedforward adaptive active noise control system.

The secondary path is essential in the design of adaptive active noise control systems, and it varies with several factors in practical implementation. In this paper, the acoustic responses from secondary loudspeakers installed at the shoulder of the front passenger seat to the error microphones at the passenger's ears in an automobile cabin are measured, when the factors including the passenger movement, the seat posture and the passenger number change. The upper limit frequency where the phase variation is within 90 deg. compared to the reference position is analyzed. The results show that the state of both the passenger head and the seat back determines the lowest upper limit frequency among all the factors under investigation. If multiple factors change at the same time, the upper limit frequency will be further reduced.

This papers aims to develop an Adaptive Feedback Active Noise Control (AFB-ANC) system comprising two adaptive filters. The first adaptive filter is the same as found in the traditional AFB-ANC systems and is adapted using the classical Filtered-x Least Mean Square (FxLMS) algorithm. The stability of the FxLMS algorithm requires filtering the reference signal via a `good' estimate of the cancellation path (CP) present between the cancellation loudspeaker and the error microphone. Since the CP may be time-varying in the practical situations, the task of the second adaptive filter is to provide estimation of the CP during operation of the AFB-ANC system. The Cancellation-Path Estimation (CPE) filter is excited by a probe signal and is adapted using a delay-based Normalized Least Mean Square (NLMS) algorithm. The proposed system is equipped with a simple strategy to monitor the convergence status of the CPE filter. The developed strategy allows to inject a large (small) probe signal during the transient (steady) state of the AFB-ANC system. Computer simulation are carried out which demonstrate the effective performance of the developed system.

The frequency-domain implementation of the adaptive LMS algorithm offers several advantages over the time-domain LMS algorithm. The primary advantage is that the orthogonality of the individual bins in the signal spectra permit the implementation of a single complex LMS filter for each FFT bin independently, each with a separate convergence parameter. The result is a uniform rate of convergence for all FFT bins as opposed to the time-domain algorithm which converges only as fast as the dominant eigenvalue of the input data. An additional parameter which affects frequency-domain LMS convergence is the overlap between successive FFT buffers. It is shown that the maximum advisable overlap between FFT buffers is 50%. Greater overlap between FFT buffers can lead to oscillations (and even instability) in the adaptive algorithm. Experimental results are presented which illustrate the convergence characteristics of a frequency-domain adaptive active noise control system for several different types of reference inputs.

Active control of road noise considering the vibro-acoustic transfer path of a passenger car

Audio-integrated feedback active noise control (AFANC) systems deliver wideband audio signals and cancel low frequency narrowband noises simultaneously. The conventional AFANC system uses single-rate processing with fullband adaptive active noise control (ANC) filter for generating anti-noise signal and fullband audio cancelation filter for audio-interference cancelation. The conventional system requires a high sampling rate for audio processing. Thus, the fullband adaptive filters require long filter lengths, resulting in high computational complexity and impracticality in real-time system. This paper proposes a multirate AFANC system using decimated-band adaptive filters (DAFs) to decrease the required filter lengths. The decimated-band adaptive ANC filter is updated by the proposed decimated filtered-X least mean square (FXLMS) algorithm, and the decimated-band audio cancelation filter can be obtained by the proposed on-line and off-line decimated secondary-path modeling algorithms. The computational complexity can be decreased significantly in the proposed AFANC system with good enough noise reduction and fast convergence speed, which were verified in the analysis and computer simulations. The proposed AFANC system was implemented for an active headrest system, and the real-time performances were tested in real-time experiments.

Beyond the delay barrier in adaptive feedforward active noise control using Youla–Kučera parametrization

Based on the theoretical analysis of literature, saturation in measured signal of active noise control (ANC) systems will degrade the convergence speed. However, the experiments show that the saturated input signal can speed up the convergence of the narrow-band ANC systems. This paper intends to remodel the saturation effects for feedforward and feedback ANC systems. Combining the action of analog-to-digital converters (ADC), the mathematical expression and block diagrams are proposed to model the saturation effects in the practical ANC systems. The derivation and simulation results show that since the saturation is able to amplify the principle component of signal, the convergence would be speeded up.

Multichannel active noise control (ANC) systems have been investigated to reduce outdoor low-frequency noise, such as power transformer noise and traffic noise. However, in outdoor environments, wind noise is inevitable and significantly degrades the noise reduction performance of active control systems. Despite broad adoption in windy environments, porous microphone windscreens cannot eliminate low-frequency wind noise in microphones, especially when the wind speed is high. Assuming wind noise is additive and uncorrelated with the primary noise to be controlled, this paper analyses how the wind noise detected by the reference microphone impacts the control filters and the residual noise of a multichannel ANC system based on the multichannel filtered-reference least mean squares algorithm (MFxLMS). By extending our recent research on wind noise suppression in single-channel active noise control systems [Y. Chu, et al., J. Acoust. Soc. Am. 152(6), 3340–3345 (2022)], a modified MFxLMS algorithm based on a new cost function is proposed. Simulations with real-recorded wind noise are performed to verify the theoretical analysis.

Multichannel feedforward active noise control system combined with noise source separation by microphone arrays

This paper presents an investigation into the development of an active control mechanism for noise cancellation and vibration suppression within an adaptive control framework. An active noise control (ANC) system is designed utilising a SIMO control structure to yield optimum cancellation of broadband noise, emanating from a point source, at a set of observation points in a linear free-field propagation medium. The controller design relations are formulated such as to allow online design and implementation and, thus, yield a self-tuning control algorithm. The algorithm is implemented on a digital processor and its performance assessed in the cancellation of broadband noise. A cantilever beam system in transverse vibration is considered for vibration suppression. Such a system has an infinite number of modes although in most cases the lower modes are the dominant ones requiring attention. The unwanted vibrations in the structure are assumed to be caused by a single point disturbance of broadband nature. These are detected and suitable suppression signals generated via point actuators to yield vibration suppression over a broad frequency range along the beam. The selftuning control algorithm developed within the ANC system is implemented within a SIMO vibration control structure and its performance assessed.< >

The infrastructure of the Klebano {Saric Wind Tunnel is upgraded in anticipation of boundary layer sound receptivity experiments. Five speakers, installed inside the tunnel, create planar, downstream-traveling sound, and multiple microphones measure the sound output in the test section. The change in wind tunnel area downstream of the test section creates a re ected, upstream-traveling wave during acoustic forcing. An active noise control system uses two speakers downstream of the test section to create upstream-traveling waves that destructively interfere with the re ections. Active noise control reduces the re ections up to 42.3 dB at 10 m/s and 33.2 dB at 20 m/s with an average reduction of 28.6 dB at 10 m/s and 23.2 dB at 20 m/s. Active noise control is also used to reduce upstreamtraveling tonal background noise up to 5.6 dB. The adaptive control system allows greater experimental control during sound receptivity experiments.

In practical active noise control (ANC) systems, the primary path and the secondary path may be nonlinear and time-varying. It has been reported that the linear techniques used to control such ANC systems exhibit degradation in performance. In addition, the actuators of an ANC system very often have nonminimum-phase response. A linear controller under such situations yields poor performance. A novel functional link artificial neural network (FLANN)-based simultaneous perturbation stochastic approximation (SPSA) algorithm, which functions as a nonlinear mode-free (MF) controller, is proposed in this paper. Computer simulations have been carried out to demonstrate that the proposed algorithm outperforms the standard filtered-x least mean square (FXLMS) algorithm, and performs better than the recently proposed filtered-s least mean square (FSLMS) algorithm when the secondary path is time-varying. This observation implies that the SPSA-based MF controller can eliminate the need of the modeling of the secondary path for the ANC system.