Active noise control (ANC) became in the last decade a very popular technique for controlling low‐frequency noise. The increase in its popularity was a consequence of the rapid development in the fields of computers in general, and more specifically in digital signal processing boards. ANC systems are application specific and therefore they should be optimally designed for each application. Even though the physical background of the ANC systems is well‐known and understood, tools for the optimization of the sensor and actuator configurations of the ANC system based on classical optimization methods do not perform as required. This is due to the nature of the problem that allows the calculation of the effect of the ANC system only when the sensor and actuator configurations are specified. An additional difficulty in this problem is that the sensor and the actuator configurations cannot be optimized independently, since the effect of the ANC system is directly involved in the combined sensor and actuator configuration. For the solution of this problem several intelligent techniques were applied. In this paper the successful application of a genetic algorithm, an optimization technique that belongs to the broad class of evolutionary algorithms, is presented.
Manolas, D.A., Borchers, I. and Tsahalis, D.T. (2000), "Simultaneous optimization of the sensor and actuator positions for an active noise and/or vibration control system using genetic algorithms, applied in a Dornier aircraft", Engineering Computations, Vol. 17 No. 5, pp. 620-630. https://doi.org/10.1108/02644400010339806
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