Acoustic feedback is the main problem associated with (broadband) active noise control (ANC) in feed-forward configuration. To solve this problem, auxiliary noise is injected into the ANC system to have accurate model of the feedback path. The conventional approaches substantially model the feedback path at the cost of degradation in the noise reduction performance (NRP) and vice versa. Here, we propose a fuzzy logic-based gain scheduling (of auxiliary noise) for online feedback path modeling and neutralization (FBPMN). The fuzzy controller computes the instantaneous gain for auxiliary noise based on two inputs, the first input gives information about modeling status of FBPMN filter while the second input gives information regarding variance of the disturbance signal for the adaptive FBPMN filter. Furthermore, variable step-size (VSS) is used for the adaptation of FBPMN filter that uses a larger value of step-size during modeling (phase) of FBPMN filter for fast adaptation and a smaller value when the feedback path has been (adequately) modeled. Fuzzy gain scheduler together with VSS in FBPMN filter improves both the NRP and feedback path modeling characteristics. Moreover, the proposed method does not require initial offline modeling of the feedback path thereby demonstrating complete online operation. To make the system computationally efficient, a look-up table-based approach is also proposed in this paper. Simulations results are presented to demonstrate the effectiveness of the proposed method.
Adaptive variable step-size neural controller for nonlinear feedback active noise control systems
