Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

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.

Active control for vehicle interior noise based on DWT-FxLMS algorithm using a piezoelectric feedback system

This paper proposes a method for shortening the distance from a noise detection microphone to a loudspeaker forming the feedforward type of active noise control (ANC) system. In the ANC system, the primary noise detected by the noise detection microphone and the secondary noise provided by the loudspeaker is required simultaneously arriving at another microphone, called error microphone, monitoring the effect of the active noise control. However, the reverberation involved in the secondary path from the loudspeaker to the error microphone increase the secondary noise components arriving later than the primary noise. The late components are not only invalid for cancelling the primary noise but also impede the cancellation. This paper hence proposes a method reducing the components by forming the noise control filter synthesizing the secondary noise with the cascade connection of an infinite and a finite impulse response filters. The distance can be thereby shortened.

Excessive noise levels inside infants incubators in neonatal intensive care units (NICU) contribute to number of harmful effects on the infant's health. This paper develops and implements practical active noise control (ANC) systems for the infant incubators. The filtered-X least mean square (FXLMS) algorithm is used to cancel the noise inside the incubator. The multi-channel and pseudo multi-channel ANC systems are proposed to enhance the noise cancellation performance in terms of cancellation gain and quiet zone. An experimental setup based on real Giraffe incubator from GE Healthcare is used for real-time experiments. The results show that the ANC system can dramatically reduce the noise and cost effective.

Impulsive noise reduction is a special problem raised in active noise control (ANC) systems. The filtered-x least mean square (FxLMS) algorithm is a typical ANC method that has been successfully applied in practical applications. Some variants such as the logarithmic FxLMS and modified FxLMS algorithms have been proposed to deal with the impulsive noise for ANC. However, those methods require considerable computational loading in real-time applications. In this paper, a modified median FxLMS method is proposed for its low complexity to avoid the effect of the impulsive noise. Simulation results show that the proposed algorithm has better averaged noise reduction performance than the conventional FxLMS and other order statistics based FxLMS algorithms. In addition, the computational complexity stays the minimum requirement through using only the ordering operation, which is very suitable for the real-time implementation.

Filtered-X least mean square (FXLMS) algorithm is widely used in active noise control (ANC) systems when the secondary path is linear. However, the performance of FXLMS reduces when nonlinearity is present. Leaky FXLMS (LFXLMS) and minimum output variance FXLMS (MOVFXLMS) algorithms are effective in compensating the nonlinearity effects in nonlinear ANC (NANC). When using optimum leakage factors, these algorithms show close performance with benchmark nonlinear FXLMS (NLFXLMS) algorithm. In all three algorithms, the degree of nonlinearity must be known in advance and are usually assumed. In previous works, Tangential Hyperbolic Function NLFXLMS (THF-NLFXLMS) algorithm has been developed whereby the degree of nonlinearity is estimated using tangential hyperbolic function (THF). In this work, the performance of LFXLMS and MOVFXLMS based on optimum leakage factors calculated using the estimated degree of nonlinearity is compared with THF-NLFXLMS for Hammerstein structure. The results show that optimum MOVFXLMS performs similarly to optimum LFXLMS and THF-NLFXLMS.

The intake system in an automotive engine has a short duct compared with that of the exhaust system. The filtered-x LMS (FX-LMS) algorithm has been applied to the active noise control (ANC) system in a short acoustic duct. This algorithm design is based on the FIR (finite impulse response) filter; however, it has a slow convergence issue due to a large number of zero coefficients. To improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct because the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filtered-u LMS algorithm (FU-LMS) based on the infinite impulse response (IIR) is developed to consider backward acoustic propagation. Generally, this algorithm has a stability problem. The stability issue was improved using an error-smoothing filter. In this paper, the recursive LMS algorithm with a variable step size and smoothing error filter is designed. This recursive LMS algorithm, the FU-VSSLMS algorithm, uses an IIR filter. With fast convergence and good stability, this algorithm is suitable for the ANC system in a short acoustic duct, such as the intake system of an automotive engine. This algorithm is applied to the ANC system of a short acoustic duct. The disturbance signals used as primary noise source are a sinusoidal signal embedded in white noise and the chirp signal, which has a variable instantaneous frequency. The test results demonstrate that the FU-VSSLMS algorithm has a superior convergence performance when compared with the FX-LMS and FX-LMS algorithms. The algorithm can be successfully applied to the ANC system in a short duct, such as the intake duct.

A robust evolutionary feedforward active noise control system using Wilcoxon norm and particle swarm optimization algorithm

All-pass filtered x least mean square algorithm for narrowband active noise control

The purpose of this study is to help reduce high noise levels experienced by patients in intensive care unit (ICU) environments. The study has designed and developed the active noise control (ANC) system based on filtered x least mean square (FxLMS) to reduce the interfering noise around ICU patients’ beds. A multi-channel feed-forward ANC algorithm has been implemented in a real-time digital signal processing system based on TMS320 DSP C6713. This noise cancellation system has been tested in a patient bed with recorded real ICU noise as the noise source to mimic the ICU noisy environment. The experiment setup has been presented. The real-time experiment results show that ANC is a promising solution to solve high noise level problem inside ICU.

The main focus of this paper is the acoustic feedback path neutralisation during online operation of the single‐channel active noise control (ANC) systems. Invasive techniques, in which additive auxiliary noise is injected for online feedback path modelling (FBPM), degrade the noise‐reduction performance of ANC systems. In the existing methods for online FBPM, additive auxiliary noise with fixed variance is injected during all operating conditions of ANC systems. In this paper, a scheduling strategy is proposed to have time‐varying gain for additive auxiliary noise. The time‐varying gain is computed on the basis of (i) the convergence status of the FBPM filter, and (ii) the power of the interference term in the error signal of the FBPM filter. Simulation results show that, compared to the existing methods, the proposed method can better achieve the conflicting requirements of fast convergence of the FBPM filter, and reduced steady‐state power of the residual error at the error microphone. For sake of completeness, appendix presents typical simulation results when both the secondary path and feedback path are simultaneously identified during online operation of ANC systems.

Cascading time-frequency domain filtered-x LMS algorithm for active control of uncorrelated disturbances

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

Stochastic analysis of FXLMS-based internal model control feedback active noise control systems