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Abstract: In this paper a multi-input, multi-output (MIMO) active noise control system with the aim of global reduction of broadband noise in a telephone kiosk is addressed. The model selected for this optimization problem is the acoustic environment of an enclosure taking into account the effect of coupling of secondary sources used for control purpose. This optimization involves finding the best locations for loudspeakers and microphones inside the enclosure as well as optimizing the control signals considering secondary source coupling. Previous results show that in order to be able to reduce acoustic noise globally inside the enclosure, the frequency range of 50–300Hz must be selected for control purpose. The mean of acoustic potential energy of the enclosure, when excited in this frequency range, is adopted as a performance measure. This performance index is penalized with the power of the signal required to excite secondary loudspeakers, in order to avoid placements that may need high voltage power amplifier for a desired performance. To find the solution of this problem, i.e. the global minimum of the performance index, several genetic algorithms are proposed and compared. In order to attain the best achievable performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and used for optimization purpose. Numerical simulations of the acoustical potential energy as well as the sound pressure at different heights of the kiosk, when active noise control (ANC) system operates, confirm the optimality of the locations proposed by the genetic algorithm. [Copyright &y& Elsevier]

The problem of optimizing an active noise control system for the implementation of a multi-channel ANC system with the aim of global reduction of broadband noise in a telephone kiosk is addressed in this paper. This optimization involves finding best locations for loudspeakers and microphones, and optimizing control signals. The problem of finding a proper size for control system, i.e. the number of loudspeakers and microphones involved in the control system is also investigated. The mean of acoustic potential energy in the enclosure in a frequency range of 50 Hz to 300 Hz is selected as a measure for optimization. Several genetic algorithms are proposed and compared to find the global minimum of this performance index. In order to have a better performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and the best genetic algorithm is selected among them. Numerical simulations of the acoustical potential energy and also sound pressure at the height where the head of a person may be located, confirms the optimality of the locations proposed by the genetic algorithm. Besides, the robustness of the optimized control system with respect to eventual changes in the location of primary and secondary loudspeakers and also microphones is shown with several simulations. [ABSTRACT FROM AUTHOR]

One of the main important aspects in designing an active control system is the optimization of position and number of sensors and actuators. In this paper this problem is addressed for the implementation of a multi-channel active noise control (ANC) system with the aim of global reduction of broadband noise in a telephone kiosk. This includes optimizing the locations for loudspeakers and microphones, finding proper size of the control system, i.e. the number of loudspeakers and microphones, and optimization of the control signals. The mean of acoustic potential energy in the enclosure in a frequency range of 50 Hz to 300 Hz is selected as the performance index for optimization purpose. Several genetic algorithms are proposed and compared to find the global minimum of this performance index. In order to have a better performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and the best genetic algorithm is selected among them. The main difference between the proposed algorithms is the used coding scheme. Numerical simulations of the acoustical potential energy and also sound pressure at the height where the head of a person may be located, confirms the optimality of the locations proposed by the genetic algorithm. [ABSTRACT FROM AUTHOR]