Yongjie Zhuang and Yangfan Liu, “A constrained adaptive active noise control filter design method via online convex optimization,” 183rd meeting of the Acoustical Society of America, December 2022, Nashville, Tennessee, USA. Abstract published in the Journal of the Acoustical Society of America 152(4), A98-A98, 2022.


In practical active noise control (ANC) applications, various types of constraints may need to be satisfied, e.g., robust stability, disturbance enhancement, and filter output power constraint. Some adaptive filters such as leaky LMS have been developed to apply required constraints indirectly. However, when multiple constraints are required simultaneously, satisfactory noise performance is difficult to achieve by tuning only one leaky factor. Another filter design approach that may achieve better noise control performance is to solve a constrained optimization problem. But the computational complexity of solving such a constrained optimization problem for ANC applications is usually too high even for offline design. Recently, a convex optimization reformulation is proposed which significantly reduces the required computational effort in solving constrained optimization problems for active noise control applications. In the current work, a constrained adaptive ANC filter design method is proposed. The previously proposed convex formulation is improved so that it can be implemented in real-time. The optimal filter coefficients are then redesigned continuously using online convex optimization when the environment is time-varying.


Active noise control, multi-channel, adaptive constrained filter design, efficient, convex optimization


Acoustics and Noise Control

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