Abstract
In this paper, a subspace identification solution is provided for active noise control (ANC) problems. The solution is related to so-called block updating methods, where instead of updating the (feedforward) controller on a sample by sample base, it is updated each time based on a block of N samples. The use of the subspace identification based ANC methods enables non-iterative derivation and updating of MIMO compact state space models for the controller. The robustness property of subspace identification methods forms the basis of an accurate model updating mechanism, using small size data batches. The design of a feedforward controller via the proposed approach is illustrated for an acoustic duct benchmark problem, supplied by TNO Institute of Applied Physics (TNO-TPD), the Netherlands. We also show how to cope with intrinsic feedback. A comparison study with various ANC schemes, such as block filtered-U, demonstrates the increased robustness of a subspace derived controller
Original language | Undefined |
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Title of host publication | Proceedings of the 39th IEEE Conference on Decision and Control |
Place of Publication | Sydney, Australia |
Publisher | IEEE |
Pages | 2397-2402 |
Number of pages | 6 |
ISBN (Print) | 9780780366381 |
DOIs | |
Publication status | Published - 15 Dec 2000 |
Event | 39th IEEE Conference on Decision and Control, CDC 2000 - Sydney Convention and Exhibition Centre , Sydney, Australia Duration: 12 Dec 2000 → 15 Dec 2000 Conference number: 39 |
Publication series
Name | |
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Publisher | IEEE |
Volume | 3 |
Conference
Conference | 39th IEEE Conference on Decision and Control, CDC 2000 |
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Abbreviated title | CDC |
Country/Territory | Australia |
City | Sydney |
Period | 12/12/00 → 15/12/00 |
Keywords
- METIS-130454
- IR-25652