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Robust performance of virtual sensing methods for active noise control

机译：有源噪声控制虚拟传感方法的鲁棒性能

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摘要

This paper investigates the effect of changes in the environment on the performance of two widely-used virtual sensing methods for active noise control (ANC): the remote-microphone method and the additional-filter method. Robust performance of adaptive feedforward control algorithms incorporating such virtual sensing techniques is essential to achieving noise attenuation at the designated locations in practice, when subject to uncertainties in the control environment. Off-line simulations using the data measured with a headrest ANC system in a running car are initially conducted, to evaluate the performance of the two virtual sensing methods under practical conditions. The differences between the two methods are further studied by using an analytical model and numerical simulations of the headrest ANC system. It is shown that in general the additional-filter method is sensitive to uncertainties in the properties of the reference signals used for feedforward control, whereas the remote-microphone method is sensitive to changes in the plant responses related to the monitoring microphones. This study, therefore, can be used to guide the choice of virtual sensing methods in different applications.
机译：本文研究了环境变化对有源噪声控制（ANC）的两个广泛使用虚拟传感方法的性能的影响：遥控器方法和附加滤波方法。结合这种虚拟感测技术的自适应前馈控制算法的鲁棒性能对于在实践中实现在实践中的指定位置处的噪声衰减是必要的，当控制环境中的不确定性时。最初进行了使用用头枕ANC系统测量的数据的离线模拟，最初进行，以在实际条件下评估两个虚拟感测方法的性能。通过使用头枕ANC系统的分析模型和数值模拟，进一步研究两种方法之间的差异。结果表明，通常，附加滤波法对用于前馈控制的参考信号的性质中的不确定性敏感，而遥控器方法对与监测麦克风相关的植物响应的变化敏感。因此，本研究可用于指导不同应用中的虚拟传感方法的选择。

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