Titre :	Adaptive feedforward controllers for active noise control
Type de document :	texte imprimé
Auteurs :	Biao Liu, Auteur
Editeur :	Germany : Shaker Verlag
Année de publication :	2001
Collection :	Berichte Aus Der Elektrotechnik
Importance :	112 p.
Présentation :	couv. ill.,ill.
Format :	24 cm.
ISBN/ISSN/EAN :	978-3-8265-8766-5
Langues :	Anglais (eng)
Catégories :	AUTOMATISME
Index. décimale :	25-07 Théorie de la commande: commandes des processus
Résumé :	Active noise control (ANC) of headsets is revisited in this paper. An in-depth electroacoustic analysis of the combined loudspeaker-cavity headset system is conducted on the basis of electro-mechano-acoustical analogous circuits. Model matching of the primary path and the secondary path leads to a feedforward control architecture. The ideal controller sheds some light on the key parameters that affect the noise reduction performance. Filtered-X least-mean-squares algorithm is employed to implement the feedforward controller on a digital signal processor. Since the relative delay of the primary path and the secondary path is crucial to the noise reduction performance, multirate signal processing with polyphase implementation is utilized to minimize the effective analog-digital conversion delay in the secondary path. Ad hoc decimation and interpolation filters are designed in order not to introduce excessive phase delays at the cutoff. Real-time experiments are undertaken to validate the implemented ANC system. Listening tests are also conducted to compare the fixed controller and the adaptive controller in terms of noise reduction and signal tracking performance for three noise types. The results have demonstrated that the fixed feedforward controller achieved satisfactory noise reduction performance and signal tracking quality.
Note de contenu :	Table des matiéres: 1 Introduction 2 ANC as a control problem and the ANC plant 3 Adaptive system identification 4 Simplified feedback representations of adaptive algorithms 5 From signal processing to control: the underlying design problem of the direct adaptive inverse controller 6 Robustness of the adaptive inverse controller 7 Direct adaptive inverse control for ANC in duct

Adaptive feedforward controllers for active noise control [texte imprimé] / Biao Liu, Auteur . - Germany : Shaker Verlag, 2001 . - 112 p. : couv. ill.,ill. ; 24 cm.. - (Berichte Aus Der Elektrotechnik) .
ISBN : 978-3-8265-8766-5
Langues : Anglais (eng)

Catégories :	AUTOMATISME
Index. décimale :	25-07 Théorie de la commande: commandes des processus
Résumé :	Active noise control (ANC) of headsets is revisited in this paper. An in-depth electroacoustic analysis of the combined loudspeaker-cavity headset system is conducted on the basis of electro-mechano-acoustical analogous circuits. Model matching of the primary path and the secondary path leads to a feedforward control architecture. The ideal controller sheds some light on the key parameters that affect the noise reduction performance. Filtered-X least-mean-squares algorithm is employed to implement the feedforward controller on a digital signal processor. Since the relative delay of the primary path and the secondary path is crucial to the noise reduction performance, multirate signal processing with polyphase implementation is utilized to minimize the effective analog-digital conversion delay in the secondary path. Ad hoc decimation and interpolation filters are designed in order not to introduce excessive phase delays at the cutoff. Real-time experiments are undertaken to validate the implemented ANC system. Listening tests are also conducted to compare the fixed controller and the adaptive controller in terms of noise reduction and signal tracking performance for three noise types. The results have demonstrated that the fixed feedforward controller achieved satisfactory noise reduction performance and signal tracking quality.
Note de contenu :	Table des matiéres: 1 Introduction 2 ANC as a control problem and the ANC plant 3 Adaptive system identification 4 Simplified feedback representations of adaptive algorithms 5 From signal processing to control: the underlying design problem of the direct adaptive inverse controller 6 Robustness of the adaptive inverse controller 7 Direct adaptive inverse control for ANC in duct