Adjoint nonlinear active noise control algorithm for virtual microphone
Controlling nonlinear noise processes at a virtual location involves higher computational complexity compared to traditional active noise control (ANC) at a physical sensor. In an attempt to reduce the computational burden, a filtered-error LMS based ANC algorithm is proposed in this paper for contr...
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| Published in | Mechanical systems and signal processing Vol. 27; pp. 743 - 754 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.02.2012
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0888-3270 1096-1216 |
| DOI | 10.1016/j.ymssp.2011.09.012 |
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| Abstract | Controlling nonlinear noise processes at a virtual location involves higher computational complexity compared to traditional active noise control (ANC) at a physical sensor. In an attempt to reduce the computational burden, a filtered-error LMS based ANC algorithm is proposed in this paper for controlling a nonlinear noise process at a virtual location. The filtered-error based algorithm using the adjoint of the secondary path is used to develop both linear and nonlinear ANC controllers with the later based on the functional link artificial neural network. A computer simulation and real-time experimental study with detailed computational complexity analysis are presented to support the proposed algorithm. |
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| AbstractList | Controlling nonlinear noise processes at a virtual location involves higher computational complexity compared to traditional active noise control (ANC) at a physical sensor. In an attempt to reduce the computational burden, a filtered-error LMS based ANC algorithm is proposed in this paper for controlling a nonlinear noise process at a virtual location. The filtered-error based algorithm using the adjoint of the secondary path is used to develop both linear and nonlinear ANC controllers with the later based on the functional link artificial neural network. A computer simulation and real-time experimental study with detailed computational complexity analysis are presented to support the proposed algorithm. |
| Author | Moreau, Danielle J. Das, Debi Prasad Cazzolato, Ben S. |
| Author_xml | – sequence: 1 givenname: Debi Prasad surname: Das fullname: Das, Debi Prasad email: debi_das_debi@yahoo.com, debi.das@adelaide.edu.au organization: The School of Mechanical Engineering, The University of Adelaide, Adelaide 5005, SA, Australia – sequence: 2 givenname: Danielle J. surname: Moreau fullname: Moreau, Danielle J. email: danielle.moreau@adelaide.edu.au organization: The School of Mechanical Engineering, The University of Adelaide, Adelaide 5005, SA, Australia – sequence: 3 givenname: Ben S. surname: Cazzolato fullname: Cazzolato, Ben S. email: benjamin.cazzolato@adelaide.edu.au organization: The School of Mechanical Engineering, The University of Adelaide, Adelaide 5005, SA, Australia |
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| Keywords | Virtual ANC Adjoint LMS FLANN Filtered-error algorithm Nonlinear ANC |
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| SubjectTerms | Active noise control Adjoint LMS Adjoints Algorithms Complexity Computation Filtered-error algorithm FLANN Noise Nonlinear ANC Nonlinearity Position (location) Virtual ANC |
| Title | Adjoint nonlinear active noise control algorithm for virtual microphone |
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