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A genetic algorithm for optimal positioning of actuators in active noise control: results from the ASANCA project

D.T. Tsahalis (D.T. Tsahalis is based at the Laboratory of Fluid Mechanics and Energy, Chemical Engineering Department, University of Patras, Patra, Greece.)
S.K. Katsikas (S.K. Katsikas is based in the Department of Mathematics, University of the Aegean, Karlovassi, Greece.)
D.A. Manolas (D.A. Manolas is based at the Laboratory of Fluid Mechanics and Energy, Chemical Engineering Department, University of Patras, Patra, Greece.)

Aircraft Engineering and Aerospace Technology

ISSN: 0002-2667

Article publication date: 1 June 2000

Abstract

In order to achieve maximum noise reduction inside an aircraft cabin through the use of an active noise control system (ANCS), it is important that the number and positions of the sensors for monitoring the noise field; the control system for driving the actuators; and the number and positions of the actuators that generate the secondary noise field, which partially cancels the primary noise field, must be optimally determined. An optimization strategy for the positioning of the actuators, based on genetic algorithms (GA), is presented, assuming a fixed sensor configuration and a given control system. The application of the developed GA to a propeller aircraft is also discussed. The work presented was performed under the CEC BRITE/EURAM‐Aeronautics project “ASANCA”, in which a demonstrator ANCS was developed.

Keywords

Citation

Tsahalis, D.T., Katsikas, S.K. and Manolas, D.A. (2000), "A genetic algorithm for optimal positioning of actuators in active noise control: results from the ASANCA project", Aircraft Engineering and Aerospace Technology, Vol. 72 No. 3, pp. 252-258. https://doi.org/10.1108/00022660010332050

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