Space Active Noise Control System Design with Multi-objective Genetic Algorithms

The model for the space active noise control system is investigated in this paper and is converted to a multi-objective optimization problem with constraints, of which the positions of secondary speakers and error sensors are the decision variables, the summation of the squared pressure at all points within the noise quiet zone and the total source strength for the secondary speakers are the multi-objective functions. The multi-objective genetic algorithms and simple genetic algorithm are implemented to solve the optimization problem so as to determine the appropriate positions of the secondary speakers and error sensors. The large sound pressure reductions within the noise quiet zone to control the single tone primary noise and motor operating noise show that the optimal schemes obtained by the multi-objective genetic algorithms are efficient.