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

2013 ◽  
Vol 135 (5) ◽  
Author(s):  
Jie Duan ◽  
Mingfeng Li ◽  
Teik C. Lim ◽  
Ming-Ran Lee ◽  
Ming-Te Cheng ◽  
...  
Keyword(s):  
Control System ◽  
Noise Control ◽  
Multiple Input Multiple Output ◽  
Active Noise Control ◽  
Least Mean Square ◽  
Multiple Channel ◽  
Fxlms Algorithm ◽  
Input Multiple Output ◽  
Dependent Property ◽  
Vehicle Powertrain

An enhanced multiple-input multiple-output (MIMO) filtered-x least mean square (FXLMS) algorithm using improved virtual secondary path is proposed as the basis for an active noise control (ANC) system for treating vehicle powertrain noise. This new algorithm is developed to overcome the limitation caused by the frequency-dependent property of the standard FXLMS algorithm and to reduce the variation of convergence speed inherent in multiple-channel cases, in order to improve the overall performance of the control system. In this study, the convergence property of the proposed algorithm is analyzed in the frequency domain in order to yield a better understanding of the physical meaning of the virtual secondary path. In practice, because of the arrangement and sensitivities of the actuators (speakers), transducers (microphones), and physical environment, the magnitude response of the main secondary paths can be very different from each other. This difference will cause difficulty in the overall convergence of the algorithm, which will result in minimal attenuation at some of the channels. The proposed channel equalized (CE) virtual secondary path algorithm is designed to tackle this difficulty by equalizing the mean magnitude level of the main secondary paths and by adjusting other secondary paths correspondingly to keep the coupling effects among the control channels unchanged. The performance of the proposed algorithm is validated by analyzing a two-input two-output active powertrain noise control system.

Active Noise Control Based on TMS320C5509

2013 ◽  
Vol 631-632 ◽  
pp. 1172-1176
Author(s):  
Yong Wei Ma ◽  
Xin Ke Gou ◽  
Xian Jun Du ◽  
Chong Yu Ren
Keyword(s):  
Control System ◽  
Real Time ◽  
Noise Control ◽  
Active Noise Control ◽  
Noise Cancellation ◽  
Real Time Control ◽  
Time Control ◽  
Active Noise ◽  
Fxlms Algorithm ◽  
Mixed Language

The feed-forward adaptive active noise control (AANC) system is presented. Firstly, the hardware project of the system is brought forward, by selecting TMS320C5509 DSP as the controller. Then, using the mixed language, the active noise real-time control system is realized, based on the FXLMS algorithm. It’s proved that a good noise cancellation is achieved by the experiment.

Active noise control for centrifugal and axial fans

2020 ◽  
Vol 68 (6) ◽  
pp. 490-500
Author(s):  
Cheng-Yuan Chang ◽  
Xiu-Wei Liu ◽  
Sen M. Kuo ◽  
Department of Electrical Engineering, Chung Y ◽  
Department of Electrical Engineering, Chung Y ◽  
...  
Keyword(s):  
Heat Dissipation ◽  
Noise Control ◽  
Active Noise Control ◽  
Least Mean Square ◽  
Motor Speed ◽  
Fan Noise ◽  
Multiple Channel ◽  
Active Noise ◽  
Centrifugal Fans ◽  
Axial Fans

Fans are widely used in industry for heat dissipation or airflow production. It is achieved by driving a motor of fan to rotate a number of blades. Most industrial fans can be categorized into one of two general types: centrifugal fans and axial fans. However, fan noise is loud when the motor speed is high. This article develops using active noise control (ANC) system to reduce noise from both centrifugal and axial fans. By integrating loudspeakers and microphones, we present multiple-channel feedback ANC structure with the filtered-X least mean square (FXLMS) algorithm to simultaneously reduce noise from the inlet and the outlet of the fans. Several realtime experiments verify that the proposed method and experimental setup not only reduces the narrowband noise but also achieves the global cancellation of the fan noise.

Active Noise Cancellation for a Three-Dimensional Enclosure by Using Multiple-Channel Adaptive Control and H∞ Control

1998 ◽  
Vol 120 (4) ◽  
pp. 958-964 ◽  
Author(s):  
M. R. Bai ◽  
Z. Lin
Keyword(s):  
Digital Signal Processor ◽  
Random Noise ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Internal Field ◽  
Least Mean Square ◽  
Control Structures ◽  
Multiple Channel ◽  
Active Noise ◽  
Fxlms Algorithm

Active noise control (ANC) techniques for a three-dimensional enclosure are compared in terms of two control structures and two control algorithms. The multiple-channel filtered-x least-mean-square (FXLMS) algorithm and the H∞ robust control algorithm are employed for controller synthesis. Both feedforward and feedback control structures are compared. The Youla’s parameterization is employed in the formulation of the multiple-channel feedback FXLMS algorithm. The algorithms are implemented using a floating-point digital signal processor (DSP). Experiments are carried out to validate the ANC approaches for attenuation of the internal field in a rectangular wooden box. Position and number of actuators and sensors are also investigated. A broadband random noise and an engine noise are chosen as the primary noises in the experiments. The experimental results indicate that the feedforward structure yields a broader band of attenuation than the feedback structure. The FXLMS control and H∞, control achieve comparable performance.

Psychoacoustic active noise control system based on empirical mode decomposition

2019 ◽  
Vol 67 (5) ◽  
pp. 332-349
Author(s):  
Yonghong Nie ◽  
Yu Liu ◽  
Guofeng Li ◽  
Ganqing Zhang
Keyword(s):  
Control System ◽  
Noise Reduction ◽  
Empirical Mode Decomposition ◽  
Noise Control ◽  
Active Noise Control ◽  
Peak Frequency ◽  
Least Mean Square ◽  
Shaping Filter ◽  
Active Noise ◽  
Mode Decomposition

A psychoacoustic active noise control (ANC) system based on empirical mode decomposition (EMD) is proposed and implemented to improve the noise reduction performance of the control system. The noise source signal is decomposed by EMD, and the psychoacoustic parameter â–œloudnessâ–? of each intrinsic mode function (IMF) is initially calculated in such a system. Thereafter, the high-pass psychoacoustic weighting filter used to shape the error and reference signals is designed adaptively and automatically according to the loudness, peak frequency, and amplitude of each IMF. Three different ANC systems are simulated, and the sound pressure levels and loudness of their residual error signals are compared. The results demonstrate that the filter designed using this method can restrain the components of noise sources with small loudness better than the A-weighting shaping filter, so that the proposed control system can improve the noise reduction compared to those of the filtered-x least mean square and A-weighting shaping filters. Finally, the computational complexity of the three ANC systems is analyzed and compared.

Research of Quantum Algorithm for Adaptive Active Noise Control System

2012 ◽  
Vol 457-458 ◽  
pp. 196-201
Author(s):  
Wei Jiang
Keyword(s):  
Control System ◽  
Adaptive Algorithm ◽  
Noise Control ◽  
Active Noise Control ◽  
Quantum Algorithm ◽  
Adaptive Controller ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Active Noise

Adaptive active noise control based on least mean square (LMS) algorithm is a linear adaptive filter so that it cannot obtain desired noise reduction. Quantum algorithm is combined with noise control to form quantum adaptive controller. Quantum adaptive algorithm is discussed completely and noise control system is simulated in order to analyze the effects of noise control.

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