无次要路径主动噪声控制系统的生物启发式与内点混合法

Muhammad Asif Zahoor RAJA; Muhammad Saeed ASLAM; Naveed Ishtiaq CHAUDHARY; Wasim Ullah KHAN

doi:10.1631/FITEE.1601028

Your Location：

Home >

Browse articles >

无次要路径主动噪声控制系统的生物启发式与内点混合法

常规文章 | Updated：2022-05-19

- 无次要路径主动噪声控制系统的生物启发式与内点混合法
  Enhanced Publication
- Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path
- 信息与电子工程前沿（英文） 2018年19卷第2期页码：246-259
- Affiliations：
  
  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
- Author bio：
  
  Muhammad Asif Zahoor RAJA, E-mail: muhammad.asif@ciit-attock.edu.pk
  [ "Muhammad Saeed ASLAM, E-mail: msaeedengr@gmail.com" ]
  [ "Naveed Ishtiaq CHAUDHARY, E-mail: naveed.ishtiaq@iiu.edu.pk" ]
  [ "Wasim Ullah KHAN, E-mail: engr_wasi47@yahoo.com" ]
- Funds：
- DOI：10.1631/FITEE.1601028
  中图分类号： TP391;O423
- 纸质出版日期：2018-02，
  
  收稿日期：2016-02-26，
  
  修回日期：2018-02-15，
- Accepted：
Scan QR Code
Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM, Naveed Ishtiaq CHAUDHARY, 等. 无次要路径主动噪声控制系统的生物启发式与内点混合法[J]. 信息与电子工程前沿（英文）, 2018,19(2):246-259.

MUHAMMAD ASIF ZAHOOR RAJA, MUHAMMAD SAEED ASLAM, NAVEED ISHTIAQ CHAUDHARY, et al. Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path. [J]. Frontiers of information technology & electronic engineering, 2018, 19(2): 246-259.
Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM, Naveed Ishtiaq CHAUDHARY, 等. 无次要路径主动噪声控制系统的生物启发式与内点混合法[J]. 信息与电子工程前沿（英文）, 2018,19(2):246-259. DOI： 10.1631/FITEE.1601028.

MUHAMMAD ASIF ZAHOOR RAJA, MUHAMMAD SAEED ASLAM, NAVEED ISHTIAQ CHAUDHARY, et al. Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path. [J]. Frontiers of information technology & electronic engineering, 2018, 19(2): 246-259. DOI： 10.1631/FITEE.1601028.

摘要

开发了一种主动噪声控制（active noise control，ANC）系统的混合计算框架，运用基于遗传算法（genetic algorithm，GA）和内点法（interior-point method，IPM）的进化计算技术，集成得到GA-IPM方法。标准ANC系统通常采用滤波扩展最小均方算法优化线性有限脉冲响应滤波器的系数，但易陷入局部极小值（localminima，LM）。本文提出的GA-IPM计算方法有效解决了上述问题。该法不易出现LM问题，且无需识别方案中ANC系统的次级路径。采用正弦、随机和复杂随机噪声干扰下的耳机ANC模型，对该方法在几种线性和非线性主级和次级路径状况下的表现进行评估。大量独立运行算法的统计分析结果验证了该方案的准确性和收敛性。

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..

关键词

主动噪声控制（ANC）过滤扩展最小均方（FXLMS）模拟计算遗传算法内点法

Keywords

Active noise control (ANC)Filtered extended least mean square (FXLMS)Memetic computingGenetic algorithmsInterior-point method

references

I Ahmad, , , MAZ Raja, , , M Bilal, , , 等. . Neural network methods to solve the Lane-Emden type equations arising in thermodynamic studies of the spherical gas cloud model. . Neur Comput Appl, , 2017. . 28((Suppl 1):):929--944. . DOI:10.1007/s00521-016-2400-yhttp://doi.org/10.1007/s00521-016-2400-y..

MT Akhtar, , , A Nishihara. . Data-reusing-based filtered-reference adaptive algorithms for active control of impulsive noise sources. . Appl Acoust, , 2015. . 9218--26. . DOI:10.1016/j.apacoust.2015.01.006http://doi.org/10.1016/j.apacoust.2015.01.006..

MT Akhtar, , , M Abe, , , M Kawamata. . A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems. . IEEE Trans Audio Speech Lang Process, , 2006. . 14((2):):720--726. . DOI:10.1109/TSA.2005.855829http://doi.org/10.1109/TSA.2005.855829..

CY Chang, , , KK Shyu. . Active noise cancellation with a fuzzy adaptive filtered-X algorithm. . IEE Proc Circ Dev Syst, , 2003. . 150((5):):416--422. . DOI:10.1049/ip-cds:20030406http://doi.org/10.1049/ip-cds:20030406..

CY Chang, , , FB Luoh. . Enhancement of active noise control using neural-based filtered-X algorithm. . J Sound Vib, , 2007. . 305((1-2):):348--356. . DOI:10.1016/j.jsv.2007.04.007http://doi.org/10.1016/j.jsv.2007.04.007..

CY Chang, , , DR Chen. . Active noise cancellation without secondary path identification by using an adaptive genetic algorithm. . IEEE Trans Instrum Meas, , 2010. . 59((9):):2315--2327. . DOI:10.1109/TIM.2009.2036410http://doi.org/10.1109/TIM.2009.2036410..

NV George, , , G Panda. . A particle-swarm-optimization-based decentralized nonlinear active noise control system. . IEEE Trans Instrum Meas, , 2012. . 61((12):):3378--3386. . DOI:10.1109/TIM.2012.2205492http://doi.org/10.1109/TIM.2012.2205492..

NV George, , , G Panda. . Advances in active noise control: a survey, with emphasis on recent nonlinear techniques. . Signal Process, , 2013. . 93((2):):363--377. . DOI:10.1016/j.sigpro.2012.08.013http://doi.org/10.1016/j.sigpro.2012.08.013..

S Gholami-Boroujeny, , , M Eshghi. . Non-linear active noise cancellation using a bacterial foraging optimisation algorithm. . IET Signal Process, , 2012. . 6((4):):364--373. . DOI:10.1049/iet-spr.2011.0092http://doi.org/10.1049/iet-spr.2011.0092..

S Gholami-Boroujeny, , , M Eshghi. . Active noise control using an adaptive bacterial foraging optimization algorithm. . Signal Image Video Process, , 2014. . 8((8):):1507--1516. . DOI:10.1007/s11760-012-0385-2http://doi.org/10.1007/s11760-012-0385-2..

A Gotmare, , , SS Bhattacharjee, , , R Patidar, , , 等. . Swarm and evolutionary computing algorithms for system identification and filter design: a comprehensive review. . Swarm Evol Comput, , 2017. . 3268--84. . DOI:10.1016/j.swevo.2016.06.007http://doi.org/10.1016/j.swevo.2016.06.007..

P Hoseini, , , MG Shayesteh. . Efficient contrast enhancement of images using hybrid ant colony optimisation, genetic algorithm, and simulated annealing. . Dig Signal Process, , 2013. . 23((3):):879--893. . DOI:10.1016/j.dsp.2012.12.011http://doi.org/10.1016/j.dsp.2012.12.011..

G Iacca, , , F Caraffini, , , F Neri. . Memory-saving memetic computing for path-following mobile robots. . Appl Soft Comput, , 2013. . 13((4):):2003--2016. . DOI:10.1016/j.asoc.2012.11.039http://doi.org/10.1016/j.asoc.2012.11.039..

SM Kuo, , , D Morgan. . Active Noise Control Systems: Algorithms and DSP Implementations. . John Wiley & Sons, Inc., New York, USA, , 1995. ..

S Kurczyk, , , M Pawelczyk. . Active noise control using a fuzzy inference system without secondary path modelling. . Arch Acoust, , 2014a. . 39((2):):243--248. . DOI:10.2478/aoa-2014-0028http://doi.org/10.2478/aoa-2014-0028..

S Kurczyk, , , M Pawełczyk. . Active noise control without secondary path modelling—varying-delay LMS approach. . IEEE 19th Int Conf on Methods and Models in Automation and Robotics, , 2014b. . p.134--139. . DOI:10.1109/MMAR.2014.6957338http://doi.org/10.1109/MMAR.2014.6957338..

MAZ Raja, , , JA Khan, , , NI Chaudhary, , , 等. . Reliable numerical treatment of nonlinear singular Flierl-Petviashivili equations for unbounded domain using ANN, GAs, and SQP. . Appl Soft Comput, , 2016a. . 38617--636. . DOI:10.1016/j.asoc.2015.10.017http://doi.org/10.1016/j.asoc.2015.10.017..

MAZ Raja, , , A Zameer, , , AU Khan, , , 等. . A new numerical approach to solve Thomas-Fermi model of an atom using bio-inspired heuristics integrated with sequential quadratic programming. . SpringerPlus, , 2016b. . 5((1):):1400DOI:10.1186/s40064-016-3093-5http://doi.org/10.1186/s40064-016-3093-5..

C Reeves. . Genetic algorithms. In: Glover FW, Kochenberger GA (Eds.), Handbook of Metaheuristics. . Springer, New York, , 2010. . p.55--82. . ..

NK Rout, , , DP Das, , , G Panda. . Particle swarm optimization based active noise control algorithm without secondary path identification. . IEEE Trans Instrum Meas, , 2012. . 61((2):):554--563. . DOI:10.1109/TIM.2011.2169180http://doi.org/10.1109/TIM.2011.2169180..

SN Sivanandam, , , SN Deepa. . Introduction to Genetic Algorithms. . Springer, Heidelberg, , 2007. ..

L Tan, , , J Jiang. . Adaptive Volterra filters for active control of nonlinear noise processes. . IEEE Trans Signal Process, , 2001. . 49((8):):1667--1676. . DOI:10.1109/78.934136http://doi.org/10.1109/78.934136..

XH Tan, , , RM Shen, , , Y Wang. . Personalized course generation and evolution based on genetic algorithms. . J Zhejiang Univ-Sci C (Comput & Electron), , 2012. . 13((12):):909--917. . DOI:10.1631/jzus.C1200174http://doi.org/10.1631/jzus.C1200174..

B Wu, , , JT Ma, , , P Wu. . Implement an indoor low frequency noise reduction system based on FXLMS algorithm. . Appl Mech Mater, , 2014. . 667440--447. . DOI:10.4028/www.scientific.net/AMM.667.440http://doi.org/10.4028/www.scientific.net/AMM.667.440..

L Zhang, , , M Lampe, , , Z Wang. . A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints. . J Zhejiang Univ-Sci C (Comput & Electron), , 2011. . 12((12):):965--975. . DOI:10.1631/jzus.C1100045http://doi.org/10.1631/jzus.C1100045..

M Zhang, , , H Lan, , , W Ser. . Cross-updated active noise control system with online secondary path modeling. . IEEE Trans Speech Audio Process, , 2001. . 9((5):):598--602. . DOI:10.1109/89.928924http://doi.org/10.1109/89.928924..

DY Zhou, , , V DeBrunner. . Efficient adaptive nonlinear filters for nonlinear active noise control. . IEEE Trans Circ Syst I, , 2007. . 54((3):):669--681. . DOI:10.1109/TCSI.2006.887636http://doi.org/10.1109/TCSI.2006.887636..

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

Dynamic task scheduling modeling in unstructured heterogeneous multiprocessor systems