Contribution
Numerical position optimization approach for sensor and actuator placement in an active noise cancelling system
* Presenting author
Abstract:
Active noise cancelling (ANC) systems are utilized in a wide range of applications to mitigate unwanted noise. The effectiveness of such systems is not only dependent on the selection of the appropriate control algorithm but also on the number and positioning of sensors and actuators. The number and placement are influenced by physical constraints, the available space and the way and manner of the ANC performance evaluation. This leads to a nonlinear optimization problem. In this study, an analytical derived cost function for the optimization process is presented. The cost function quantifies the performance of the ANC system based on the arrangement of sensors and actuators with a specified evaluation within the given constraints. A suitable optimization algorithm, tailored to solve the specific problem, is introduced. The optimization is carried out using measurement data from a real-world experimental setup. The optimization results are subsequently validated through additional measurements, allowing for a thorough evaluation of the system's performance. The study demonstrates the potential for noise reduction through optimized sensor and actuator placement, offering insights into the design of more efficient ANC systems. The approach presented can be generalized to various ANC applications, highlighting its broad applicability.