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

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.

A Genetic Algorithm for the Simultaneous Optimization of the Sensor and Actuator Positions for an Active Noise and/or Vibration Control System

“…Among the two parans and the two o 'springs, the two bat string were kept for the next population. This crossover operator has bee-r applied suwess rlly to similar optimization problems by the LFME team [3], [4]. -Mutation.…”

Development of an Expert System Shell Based on Genetic Algorithms for the Selection of the Energy Best Available Technologies and their Optimal Operating Conditions for the Process Industry

“…All these favourable characteristics made GAs quite popular for solving difficult and/or very large problems. The Laboratory of Fluid Mechanics and Energy has developed and applied GAs in very large and complex, combinatorial (Tsahalis et al, 1993;Katsikas et al, 1995) and multidimensional (Manolas et al, 1996(Manolas et al, , 1997 optimization problems.…”

“…After the crossing was performed, among the two parents and the two offspring, the two best strings were kept for the next population (elitism). The use of elitism in the crossover operator has been applied successfully at the Laboratory of Fluid Mechanics and Energy (Tsahalis et al, 1993;Katsikas et al, 1995). ț Mutation.…”

A Comparative Study of Methods for Optimising Sensor and Actuator Locations in Active Control Applications

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