Genetic Optimization in Nonlinear Systems for Active Noise Control: Accuracy and Performance Evaluation

Author

Russo, Fabrizio ; Sicuranza, Giovanni L.

Author_Institution

D.E.E.I., Trieste Univ.

fYear

2006

fDate

24-27 April 2006

Firstpage

1512

Lastpage

1517

Abstract

This paper investigates the performance of genetic optimization in a nonlinear system for active noise control based on Volterra filters. While standard filtered-X algorithms can converge to local minima, genetic algorithms may handle this problem efficiently. In addition, this class of algorithms does not require the identification of the secondary paths. Computer simulations show that the proposed approach gives more accurate results than other techniques in the literature

Keywords

active noise control; genetic algorithms; nonlinear control systems; nonlinear filters; nonlinear systems; Volterra filters; active noise cancellation; active noise control; filtered-X algorithms; genetic algorithms; genetic optimization; nonlinear filters; nonlinear systems; Acoustic noise; Active noise reduction; Control systems; Error correction; Genetics; Low-frequency noise; Microphones; Noise cancellation; Nonlinear control systems; Nonlinear systems; Active noise cancellation; Volterra filters; genetic algorithms; nonlinear filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2006. IMTC 2006. Proceedings of the IEEE

Conference_Location

Sorrento

ISSN

1091-5281

Print_ISBN

0-7803-9359-7

Electronic_ISBN

1091-5281

Type

conf

DOI

10.1109/IMTC.2006.328650

Filename

4124598