Global Active Noise Control of a One-Dimensional Acoustic Duct Using a Feedback Controller

1993 ◽  
Vol 115 (3) ◽  
pp. 488-494 ◽  
Author(s):  
A. J. Hull ◽  
C. J. Radcliffe ◽  
S. C. Southward
Keyword(s):  
Noise Level ◽  
Noise Control ◽  
Acoustic Noise ◽  
Active Noise Control ◽  
Decay Rates ◽  
Pole Placement ◽  
Noise Levels ◽  
One Dimensional ◽  
Active Noise ◽  
System Pressure

Active noise control of acoustic enclosures is a classical engineering problem. The active noise control of a one-dimensional hard-walled duct with a partially dissipative boundary condition is addressed in this paper. Previous techniques have attacked this problem by developing adaptive filters designed to cancel acoustic noise at a single measurement location. The work presented here applies modern, state space, control theory to globally reduce noise levels in a one-dimensional acoustic enclosure rather than at a single location. This global control requires only the addition of a single response measurement microphone and control speaker to the open-loop system. Pressure measurements are taken at the microphone location and passed to an observer, which generates estimates of the system states. Using these state estimates, a pole placement feedback control algorithm is used to lower the noise level. Pole placement reduces noise levels globally by increasing the decay rates of all the controlled acoustic states. Experimental results presented here demonstrate reduction in the noise level at all points in the duct by 58 percent when the system is excited by random amplitude pressure input.

Noise Reduction in Ducts Achievable by Point Control

1998 ◽  
Vol 120 (2) ◽  
pp. 216-223 ◽  
Author(s):  
K. A. Morris
Keyword(s):  
Noise Reduction ◽  
Closed Loop ◽  
Noise Control ◽  
Active Noise Control ◽  
Practical Interest ◽  
Noise Levels ◽  
Sensors And Actuators ◽  
One Dimensional ◽  
Active Noise ◽  
Point Control

Noise control in a one-dimensional duct is analyzed. This problem is of practical interest and is also simple enough that a complete theoretical analysis is possible. It is shown that the optimal controller leads to an unstable closed loop. The noise reduction level achievable with a stable closed loop is calculated for arbitrary choices of sensor and actuator locations. This enables the best placement of sensors and actuators to be determined. Also, the analysis indicates that a “spatial waterbed” effect exists in some configurations of active noise control: i.e., that noise levels are increased for points outside of the region over which the design is done.

scholarly journals Multichannel Feedforward Active Noise Control System with Optimal Reference Microphone SelectorBased on Time Difference of Arrival

2018 ◽  
Vol 8 (11) ◽  
pp. 2291 ◽  
Author(s):  
Kenta Iwai ◽  
Satoru Hase ◽  
Yoshinobu Kajikawa
Keyword(s):  
Noise Control ◽  
Acoustic Noise ◽  
Control Point ◽  
Active Noise Control ◽  
Broadband Noise ◽  
Time Difference ◽  
Arrival Direction ◽  
Noise Sources ◽  
Time Difference Of Arrival ◽  
Active Noise

In this paper, we propose a multichannel active noise control (ANC) system with an optimal reference microphone selector based on the time difference of arrival (TDOA). A multichannel feedforward ANC system using upstream reference signals can reduce various noises such as broadband noise by arranging reference microphones close to noise sources. However, the noise reduction performance of an ANC system degrades when the noise environment changes, such as the arrival direction. This is because some reference microphones do not satisfy the causality constraint that the unwanted noise propagates to the control point faster than the anti-noise used to cancel the unwanted noise. To solve this problem, we propose a multichannel ANC system with an optimal reference microphone selector. This selector chooses the reference microphones that satisfy the causality constraint based on the TDOA. Some experimental results demonstrate that the proposed system can choose the optimal reference microphones and effectively reduce unwanted acoustic noise.

scholarly journals Sequentially Adapted Parallel Feedforward Active Noise Control of Noisy Sinusoidal Signals

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
Govind Kannan ◽  
Issa M. S. Panahi ◽  
Richard W. Briggs
Keyword(s):  
Noise Control ◽  
Acoustic Noise ◽  
Random Noise ◽  
Active Noise Control ◽  
Superior Performance ◽  
Filter Method ◽  
Periodic Signal ◽  
Noise Component ◽  
Periodic Noise ◽  
Active Noise

A large class of acoustic noise sources has an underlying periodic process that generates a periodic noise component, and thus their acoustic noise can in general be modeled as the sum of a periodic signal and a randomly fluctuating signal (usually a broadband background noise). Active control of periodic noise (i.e., for a mixture of sinusoids) is more effective than that of random noise. For mixtures of sinusoids in a background broadband random noise, conventional FXLMS-based single filter method does not reach the maximum achievable Noise Attenuation Level (NALmax⁡). In this paper, an alternative approach is taken and the idea of a parallel active noise control (ANC) architecture for cancelling mixtures of periodic and random signals is presented. The proposed ANC system separates the noise into periodic and random components and generates corresponding antinoises via separate noise cancelling filters, and tends to reach NALmax⁡ consistently. The derivation of NALmax⁡ is presented. Both the separation and noise cancellation are based on adaptive filtering. Experimental results verify the analytical development by showing superior performance of the proposed method, over the single-filter approach, for several cases of sinusoids in white noise.

scholarly journals ACTIVE NOISE CONTROL USING NEURAL SYSTEM

2010 ◽  
Vol 13 (3) ◽  
pp. 67-74
Author(s):  
Tuan Van Huynh ◽  
Nghĩa Hoai Duong
Keyword(s):  
Noise Control ◽  
Acoustic Noise ◽  
Active Noise Control ◽  
Neural System ◽  
Control Area ◽  
New Method ◽  
Traditional Methods ◽  
Active Noise ◽  
Opposite Phase ◽  
Simulation Results

The principle of active noise control (ANC) is to produce a secondary acoustic noise which has the same magnitude as the unwanted primary noise but with opposite phase. The sum of these two signals reduces acoustic noise in the noise control area. In this paper we present a new ANC method using neural system. Moreover a new method for compensating the saturation of the power applifier is also introduced. The performance of the proposed method is compared to that of traditional methods. Simulation results are provided for illustration.

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