A Virtual Sensing Active Noise Control System Based on a Functional Link Neural Network for an Aircraft Seat Headrest

Abstract Purpose The goal of this work is to propose a local Active Noise Control system for an aircraft seat’s headrest. This should be able extend the quiet zone beyond physical microphones that can placed behind passenger’s head due space constraints. Furthermore, control algorithm perform efficiently when non-linear phenomena exist during sound propagation. Methods A functional link neural network and computationally efficient Multiple Input Output approach are used system’s implementation. extended by linearly estimating acoustic pressure in front headrest surface. main novelty paper combination these methods attempt improve attenuation performance, while keeping computational complexity low. Results proposed has been evaluated through numerical simulations, including Finite Element Method experimental tests at cabin mock-up. results show real-world disturbance, 10 dB reduction level was achieved cm away from In addition, some harmonics reach 20 most cases bigger than linear FxLMS algorithm. Conclusions To summarize, it demonstrated multichannel using simple virtual sensing technique attenuate synthesized real world disturbances captured tilt-rotor aircraft’s cabin. Finally, create adequate gentle movement maintaining its stability.