Feed-Forward and Feedback Active Noise Control System Using FxLMS Algorithm for Narrowband and Broadband Noise

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.

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A two-channel feedback active noise control system with delayless subband architecture to reduce compressor noise of an enclosed heating, ventilation and air conditioning unit

Journal of Vibration and Control ◽

10.1177/1077546313499058 ◽

2013 ◽

Vol 21 (7) ◽

pp. 1430-1442 ◽

Cited By ~ 1

Author(s):

Prashanth Kasbekar ◽

Alan Wisler ◽

Issa MS Panahi

Keyword(s):

Control System ◽

Air Conditioning ◽

Noise Control ◽

Active Noise Control ◽

Active Noise ◽

Channel Feedback ◽

Feedback Active Noise Control

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Optimal parametric design of delayless subband active noise control system based on genetic algorithm optimization

Journal of Vibration and Control ◽

10.1177/10775463211001625 ◽

2021 ◽

pp. 107754632110016

Author(s):

Guo Long ◽

Yawen Wang ◽

Teik C Lim

Keyword(s):

Genetic Algorithm ◽

Control System ◽

Noise Control ◽

Parametric Design ◽

Active Noise Control ◽

Low Frequency ◽

Broadband Noise ◽

Algorithm Optimization ◽

Genetic Algorithm Optimization ◽

Active Noise

Active noise control systems are generally application-specific, and an appropriate algorithm with an optimal configuration is desirable in the first stage of active noise control system design and deployment. This study presents a design of the subband active noise control system with optimal parameters for a practical broadband active noise control. Although the delayless subband active noise control has gained wide attention for broadband noise cancellation, an optimal design remains a challenge because of the complex interplay between multiple factors such as spectral leakage, delay and weight stacking distortion subject to a number of configurable parameters, and weight stacking method. The configurable parameters can hardly be optimized independently because the active noise control performance depends on the combined configuration. A simple near black box active noise control algorithm optimization model is thus established by incorporating the genetic algorithm optimization into the parametric design of the delayless subband algorithm. The automated process does not require an understanding of the performance characteristics for different parameters. The significance of applying the automated genetic algorithm optimization to the complex multiparameter nonlinear active noise control design is revealed by numerical simulations, particularly for the multichannel low-frequency broadband active noise control system configured with the delayless subband algorithms. This provides a way for the optimal parametric design of subband active noise control before being used in a practical complex scenario.

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