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Shock and Vibration
Volume 2017 (2017), Article ID 7289076, 6 pages
Research Article

Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

1School of Electrical Information Engineering, Henan Institute of Engineering, Zhengzhou 451191, China
2School of Computer, Henan Institute of Engineering, Zhengzhou 451191, China

Correspondence should be addressed to Zhuangzhi Guo

Received 21 September 2016; Revised 26 November 2016; Accepted 19 December 2016; Published 29 January 2017

Academic Editor: Jeong-Hoi Koo

Copyright © 2017 Quanzhen Huang et al. 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.


Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS) algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP) TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.