Adaptive Active Noise Suppression Using Multiple Model Switching Strategy
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 i...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2017/7289076 |
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| _version_ | 1832566990224490496 |
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| author | Quanzhen Huang Suxia Chen Mingming Huang Zhuangzhi Guo |
| author_facet | Quanzhen Huang Suxia Chen Mingming Huang Zhuangzhi Guo |
| author_sort | Quanzhen Huang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c192f367fe4743cebadca4df4eebc009 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-c192f367fe4743cebadca4df4eebc0092025-02-03T01:02:39ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/72890767289076Adaptive Active Noise Suppression Using Multiple Model Switching StrategyQuanzhen Huang0Suxia Chen1Mingming Huang2Zhuangzhi Guo3School of Electrical Information Engineering, Henan Institute of Engineering, Zhengzhou 451191, ChinaSchool of Computer, Henan Institute of Engineering, Zhengzhou 451191, ChinaSchool of Electrical Information Engineering, Henan Institute of Engineering, Zhengzhou 451191, ChinaSchool of Electrical Information Engineering, Henan Institute of Engineering, Zhengzhou 451191, ChinaActive 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.http://dx.doi.org/10.1155/2017/7289076 |
| spellingShingle | Quanzhen Huang Suxia Chen Mingming Huang Zhuangzhi Guo Adaptive Active Noise Suppression Using Multiple Model Switching Strategy Shock and Vibration |
| title | Adaptive Active Noise Suppression Using Multiple Model Switching Strategy |
| title_full | Adaptive Active Noise Suppression Using Multiple Model Switching Strategy |
| title_fullStr | Adaptive Active Noise Suppression Using Multiple Model Switching Strategy |
| title_full_unstemmed | Adaptive Active Noise Suppression Using Multiple Model Switching Strategy |
| title_short | Adaptive Active Noise Suppression Using Multiple Model Switching Strategy |
| title_sort | adaptive active noise suppression using multiple model switching strategy |
| url | http://dx.doi.org/10.1155/2017/7289076 |
| work_keys_str_mv | AT quanzhenhuang adaptiveactivenoisesuppressionusingmultiplemodelswitchingstrategy AT suxiachen adaptiveactivenoisesuppressionusingmultiplemodelswitchingstrategy AT mingminghuang adaptiveactivenoisesuppressionusingmultiplemodelswitchingstrategy AT zhuangzhiguo adaptiveactivenoisesuppressionusingmultiplemodelswitchingstrategy |