SELECTION STRATEGIES FOR CENTRALIZED ACTIVE STRUCTURAL ACOUSTIC CONTROL OF A CASING BASED ON SYSTEM IDENTIFICATION DATA

Active Structural Acoustic Control (ASAC) is a technique designed to minimize the acoustic radiation emitting from operating machines or devices. It employs an encapsulated structure, sensors to capture the noise, and actuators to control surface vibrations. This paper analyses two selection strategies to optimize a centralized ASAC system. The main purpose is to reduce the computational complexity by limiting the amount of secondary path FIR models utilized in the system. The strategies are thoroughly examined and discussed in section 2, complemented by illustrative figures to provide visual clarity. A numerical model was created in MATLAB program to carry out simulations. Each simulation was performed with a different strategy, where the amount and order of the secondary path models differed. The numerical model uses the Normalized Multiple Error Filtered-X Least Mean Square (NMEFxLMS) as the control algorithm for the simulations presented in this paper. An optimization margin was deduced from the simulations conducted. Subsequently, the computational complexity was determined for both strategies based on deducted optimization margins.