Abstract
The reference and error sensors of active noise control (ANC) systems may be saturated in real-world applications if the noise level exceeds the dynamic range of the sensors. This nonlinear saturation degrades the performance of ANC systems that use adaptive linear filters with the filtered-X least-mean-square (FXLMS) algorithm. This paper derives adaptive nonlinear Volterra and bilinear filters with the corresponding FXLMS algorithms for solving the sensor saturation and other nonlinear distortions occurred in ANC systems for practical applications. The performance of these adaptive nonlinear filters is evaluated in terms of convergence speed and residual noise in steady state. Computer simulations using transfer functions measured from an experimental setup verify that these adaptive nonlinear algorithms are effective in reducing saturation effects in ANC systems.
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