Nonlinear Active Noise Control Using Adaptive Wavelet Filters
Keywords:
Active noise control, Wavelet filters, Nonlinear system identification, Adaptive systems.Abstract
This paper deals with nonlinear active noise control using adaptive wavelet filters. The ability of wavelets in signal reconstruction and function approximation make them appealing for black box system identification. Moreover, the intrinsic similarity between wavelet filters and noise/vibration signals implies that better approximation of these signals can be achieved by employing wavelet filters. Here, a new simple structure for using in active noise control system is proposed comprises a nonlinear static mapping cascaded with an IIR filter to take care of the dynamics of the system. With this strategy, one can avoid using multi-dimensional wavelet networks and thus eliminate curse of dimensionality. The performance of the proposed ANC system is examined for typical linear/nonlinear cases. The simulation results demonstrate superior performance of this method in terms of fast convergence rate and noise attenuation as well as computational complexity reduction while avoiding curse of dimensionality.
References
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[20] M. Akraminia, M. Mahjoob, M. Ghadami, "Nonlinear active noise control using adaptive rational functions with second-order poles frames: Simulation and experimental results," Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 229, pp. 1708-1723, 2015.
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[27] Y. L. Zhou, Q. Z. Zhang, X. D. Li, W. S. Gan, "Analysis and DSP implementation of an ANC system using a filtered-error neural network," Journal of Sound and Vibration, vol. 285, pp. 1-25, 2005.
[2] L. Tan, J. Jiang, “Adaptive Volterra filters for active control of nonlinear noise processes,” Signal Processing, IEEE Transactions on, vol. 49, pp. 1667-1676, 2001.
[3] N. Nasrollahzadeh, M. Fard, M. Tatari, “Parametric resonance: Application on low noise mechanical and electromechanical amplifiers,” in Nonlinear Approaches in Engineering Applications 2, R. Jazar, L. Dai, Ed. New York: Springer, 2014, pp. 277-308.
[4] M. Tatari, M. Fard, N. Nasrollahzadeh, M. Mahjoob. “Nonlinear Vehicle Seat BSR Characterization Using CAE Methodology” in Nonlinear Approaches in Engineering Applications 2, R. Jazar, L. Dai, Ed. New York: Springer, 2014, pp. 231-256.
[5] M. Tatari, M. Fard, N. Nasrollahzadeh, M. Mahjoob, “CAE characterization and optimization of automotive seat rattle noise,” World Journal of Engineering and Technology, vol. 2, pp. 201-210, 2014.
[6] S. M. Kuo, H. T. Wu, “Nonlinear adaptive bilinear filters for active noise control systems,” Circuits and Systems I: Regular Papers, IEEE Transactions on, vol. 52, pp. 617-624, 2005.
[7] S. D. Snyder, N. Tanaka, “Active control of vibration using a neural network,” Neural Networks, IEEE Transactions on, vol. 6, pp. 819-828, 1995.
[8] N. V. George, G. Panda, “Advances in active noise control: A survey, with emphasis on recent nonlinear techniques,” Signal Processing, vol. 93, pp. 363-377, 2013.
[9] M. Tokhi, R. Wood, “Active noise control using radial basis function networks,” Control Engineering Practice, vol. 5, pp. 1311-1322, 1997.
[10] K. T. Chen, C. H. Chou, S. H. Chang, Y. H. Liu, "Adaptive fuzzy neural network control on the acoustic field in a duct," Applied Acoustics, vol. 69, pp. 558-565, 2008.
[11] H. Zhao, X. Zeng, Z. He, T. Li, W. Jin, "Nonlinear adaptive filter-based simplified bilinear model for multichannel active control of nonlinear noise processes," Applied Acoustics, vol. 74, pp. 1414-1421, 2013.
[12] O. Asgari Gashteroodkhani, B. Vahidi, A. Zaboli, “Time-time matrix z-score vector-based fault analysis method for series-compensated transmission lines,” Turkish Journal of Electrical Engineering & Computer Sciences, vol. 25, pp. 2647-2659, 2017.
[13] N. V. George, G. Panda, "Active control of nonlinear noise processes using cascaded adaptive nonlinear filter," Applied Acoustics, vol. 74, pp. 217-222, 2013.
[14] N. V. George, A. Gonzalez, "Convex combination of nonlinear adaptive filters for active noise control," Applied Acoustics, vol. 76, pp. 157-161, 2014.
[15] S. Dashti, Z. Alzahra, M. Jafari, M. Gholami, M. A. Shoorehdeli, “Neural adaptive control based on backstepping and feedback linearization for electro hydraulic servo system,” in Intelligent Systems (ICIS), 2014 Iranian Conference on. Bam: IEEE, pp. 1–6, 2014.
[16] Z. A. S. Dashti, Zohreh, M. Jafari, M. Gholami, M. A. Shoorehdeli, M. Teshnehlab, "Speed control of a Digital Servo System using parallel distributed compensation controller and Neural Adaptive controller," 13th Iranian Conference on Fuzzy Systems (IFSC), pp. 1-6, 27-29 Aug. 2013.
[17] Z. A. S. Dashti, M. Gholami, M. Jafari, M. A. Shoorehdeli, Hajimani, "Neural Adaptive controller for Magnetic levitation system", Iranian Conference on Intelligent Systems, Bam, Iran, 2014.
[18] C.-Y. Chang, "Simple approaches to improve the performance of noise cancellation," Journal of Vibration and Control, vol. 15, pp. 1875-1883, 2009.
[19] M. Akraminia, M. J. Mahjoob, M. Tatari, "Active noise control using adaptive POLYnomial Gaussian WinOwed wavelet networks," Journal of Vibration and Control, vol. 21, pp. 3020-3033 January 28, 2014.
[20] M. Akraminia, M. Mahjoob, M. Ghadami, "Nonlinear active noise control using adaptive rational functions with second-order poles frames: Simulation and experimental results," Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 229, pp. 1708-1723, 2015.
[21] M. Akraminia, M. J. Mahjoob, A. H. Niazi, "Feedforward active noise control using wavelet frames: simulation and experimental results," Journal of Vibration and Control, vol. 23, pp. 555-573, 2017.
[22] M. Akraminia, M. J. Mahjoob, "Adaptive feedback active noise control using wavelet frames: simulation and experimental results," Journal of Vibration and Control, vol. 22, pp. 1895-1912, 2016.
[23] S. Mallat, A wavelet tour of signal processing: Academic press, 1999.
[24] I. Daubechies, Ten lectures on wavelets vol. 61: SIAM, 1992.
[25] G. Lekutai, "Adaptive self-tuning neuro wavelet network controllers," Virginia Polytechnic Institute and State University, 1997.
[26] S. A. Imhoff, D. Y. Roeum, M. R. Rosiek, "New classes of frame wavelets for applications," in SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, pp. 923-934.
[27] Y. L. Zhou, Q. Z. Zhang, X. D. Li, W. S. Gan, "Analysis and DSP implementation of an ANC system using a filtered-error neural network," Journal of Sound and Vibration, vol. 285, pp. 1-25, 2005.
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Published
2017-11-06
How to Cite
Akraminia, M., J. Mahjoob, M., & Tatari, M. (2017). Nonlinear Active Noise Control Using Adaptive Wavelet Filters. American Scientific Research Journal for Engineering, Technology, and Sciences, 37(1), 287–304. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/3542
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