Active noise control using an adaptive bacterial foraging optimization algorithm

作者：Gholami Boroujeny Shiva^*; Eshghi Mohammad

来源：Signal, Image and Video Processing, 2014, 8(8): 1507-1516.

DOI：10.1007/s11760-012-0385-2

• Active noise control (ANC)
• Adaptive filter
• Optimization algorithms
• Bacterial foraging optimization (BFO)
• Adaptive bacterial foraging optimization (ABFO)

This paper presents an adaptive bacterial foraging optimization (ABFO) algorithm for an active noise control system. The conventional active noise control (ANC) systems often use the gradient-based filtered-X least mean square algorithms to adapt the coefficients of the adaptive controller. Hence, there is a possibility to converge to local minima. In addition, this class of algorithms needs prior identification of the secondary path. The ABFO algorithm helps the ANC system to prevent falling into local minima. The proposed ANC system is also simpler since it does not need any prior information of the secondary path. Moreover, the adaptive strategy of the algorithm results in improved search performance compared with the basic bacterial foraging optimization algorithm, as well as other conventional algorithms. Experimental studies are performed for nonlinear primary path along with linear and nonlinear secondary path. The results show the effectiveness of the proposed ABFO-based ANC system for different kinds of input noise.

• 出版日期2014-11