scholarly journals Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Quanzhen Huang ◽  
Suxia Chen ◽  
Mingming Huang ◽  
Zhuangzhi Guo

Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS) algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP) TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
Liang Wang ◽  
Woon Seng Gan ◽  
Sen M. Kuo

With the advancement of digital signal processing technologies, consumers are more concerned with the quality of multimedia entertainment in automobiles. In order to meet this demand, an audio enhancement system is needed to improve bass reproduction and cancel engine noise in the cabins. This paper presents an integrated active noise control system that is based on frequency-sampling filters to track and extract the bass information from the audio signal, and a multifrequency active noise equalizer to tune the low-frequency engine harmonics to enhance the bass reproduction. In the noise cancellation mode, a maximum of 3 dB bass enhancement can be achieved with significant noise suppression, while higher bass enhancement can be achieved in the bass enhance mode. The results show that the proposed system is effective for solving both the bass audio reproduction and the noise control problems in automobile cabins.


2021 ◽  
Vol 263 (4) ◽  
pp. 2896-2904
Author(s):  
Hakjun Lee ◽  
Youngjin Park

Active noise control system has received its attention in various technical field such as headphone, motor vehicle, etc. Meanwhile, filtered-x least mean square (FxLMS) algorithm is conventional linear algorithm used in active noise control system. It assumes that acoustic path from the noise source and control source to target area are linear. However, in actual system, the secondary path including a D/A converter, an amplifier, and an actuator may exhibits nonlinear distortion like saturation effects. To cope with this nonlinear effects, functional link artificial neural network (FLANN) has been proposed. FLANN uses nonlinear function expansion filter with FxLMS based control algorithm to control the nonlinear effect. In this paper, noise reduction performance and convergence speed are improved by modifying the conventional FLANN algorithm by decoupling the linear and nonlinear part of noise signal.


2013 ◽  
Vol 364 ◽  
pp. 275-279 ◽  
Author(s):  
Chun Ming Pei ◽  
Jiang Tao Liu ◽  
Zhen Yu Liu ◽  
Li Ming Ying

Active noise control system on power equipment is designed. The paper gives overall analysis of the structure of the system. Adaptive control algorithm of control system is designed and simulated by CCS3.3. With other parameters of the system fixed, control effect of the system is analyzed by changing the filter order. As can be seen from the experimental effect, good control effect can be obtained when appropriate parameters are selected.


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