Frontiers of Information Technology & Electronic Engineering
>> 2018,
Volume 19,
Issue 2
doi:
10.1631/FITEE.1601028
Orginal Article
Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path
. Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock Campus, Attock 43600, Pakistan.. Pakistan Institute of Engineering and Applied Sciences, Islamabad 45650, Pakistan.. Department of Electronic Engineering, International Islamic University, Islamabad 44000, Pakistan.
Available online: 2018-04-23
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Abstract
In this study, hybrid computational frameworks are developed for active noise control (ANC) systems using an evolutionary computing technique based on genetic algorithms (GAs) and interior-point method (IPM), following an integrated approach, GA-IPM. Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for optimization of coefficients for the linear finite-impulse response filter, but are likely to become trapped in local minima (LM). This issue is addressed with the proposed GA-IPM computing approach which is considerably less prone to the LM problem. Also, there is no requirement to identify a secondary path for the ANC system used in the scheme. The design method is evaluated using an ANC model of a headset with sinusoidal, random, and complex random noise interferences under several scenarios based on linear and nonlinear primary and secondary paths. The accuracy and convergence of the proposed scheme are validated based on the results of statistical analysis of a large number of independent runs of the algorithm.
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