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Shock and Vibration - Volume 16 2009, Issue 3, Pages 325-334



Department of Computer Science and Automation, Beijing Institute of Machinery, P.O. Box 2865, Beijing, 100192, China

Institute of Acoustics, Academia Sinica, China

School of EEE, Nanyang Technological University, Singapore

Received 13 July 2007

Copyright © 2009 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In practical active noise control ANC systems, the primary path and the secondary path may be nonlinear and time-varying. It has been reported that the linear techniques used to control such ANC systems exhibit degradation in performance. In addition, the actuators of an ANC system very often have nonminimum-phase response. A linear controller under such situations yields poor performance. A novel functional link artificial neural network FLANN-based simultaneous perturbation stochastic approximation SPSA algorithm, which functions as a nonlinear mode-free MF controller, is proposed in this paper. Computer simulations have been carried out to demonstrate that the proposed algorithm outperforms the standard filtered-x least mean square FXLMS algorithm, and performs better than the recently proposed filtered-s least mean square FSLMS algorithm when the secondary path is time-varying. This observation implies that the SPSA-based MF controller can eliminate the need of the modeling of the secondary path for the ANC system.





Autor: Ya-li Zhou, Qi-zhi Zhang, Tao Zhang, Xiao-dong Li, and Woon-seng Gan

Fuente: https://www.hindawi.com/



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