• Title/Summary/Keyword: 오버올 모델링 기법

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Performance Improvement of the Inverse Modeling using Adaptive Line Enhancer (적응 선형 증진기를 이용한 인버스 모델링의 성능향상)

  • Kim, Heung-Sub;Hong, Jin-Seok;Son, Dong-Gu;Shin, Jun;Oh, Jae-Eung
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.267-271
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    • 1996
  • In this study, performance improvement of the inverse modeling as the on-line control method for the estimation, control experiment is performed. As the modeling errors is occurred in duct system arbitrarily, a case using the filtered-x LMS algorithm only as the control method, a case using tile inverse modeling method only and a case using the inverse modeling with the adaptive line enhancer are compared. The estimation errors between real secondary path transfer functions and the estimated and the control performances of primary noises with these estimated transfer functions are compared.

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Active noise control with on-line adaptive algorithm in a duct system (덕트에서 온라인 적응 알고리듬을 이용한 능동소음제어)

  • Kim, Heung-Seob;Hong, Jin-Seok;Oh, Jae-Eung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.8
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    • pp.1332-1338
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    • 1997
  • In the case of the transfer function for the secondary path is dependent on time, the on-line method which can model it is continuously must be applied to the active noise control technique. And the adaptive random noise technique among the on-line methods is effective in the narrow-band control. In this method, the signal to noise ratio between random noise for modeling and primary noise is low. Therefore, the estimations of transfer function will be prone to inaccuracies and the convergence time will be too long. Such imperfections will have an influence upon the performance of an active noise controller. In this study, t enhance the signal to noise ratio, the on-line method that is combined the conventional adaptive random noise technique and the adaptive line enhancer, is proposed. By using proposed on-line method, a rigorous system identification and control of primary noise have been implemented.