Robust performance of virtual sensing methods for active noise control

• Published in: Mechanical systems and signal processing Vol. 152; p. 107453
• Main Authors: Zhang, Jin, Elliott, Stephen J., Cheer, Jordan
• Format: Journal Article
• Language: English
• Published: Berlin Elsevier Ltd 01.05.2021; Elsevier BV
• Subjects: Active noise control; Adaptive algorithms; Adaptive control; Adaptive filters; Attenuation; Computer simulation; Control algorithms; Feedforward control; In-car measurement; Mathematical models; Methods; Microphones; Noise control; Performance evaluation; Reference signals; Remote control; Remote sensing; Robust performance; Robustness (mathematics); Uncertainty; Virtual sensing; Robust performance; Virtual sensing; In-car measurement; Active noise control
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2020.107453

•The performance of two widely used virtual sensing methods for ANC are presented.•Of particular interest is their robust performance when subject to uncertainty.•Results from measurement and numerical model agree well with analytical results.•The remote-microphone method is sensitive to uncertainties in the plant responses.•The additional-filter method is sensitive to uncertainties in the reference signals. 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.