A method for noninvasive on-line secondary path modeling for the filtered-X LMS algorithm for active control of periodic noise

A novel method for noninvasive on-line secondary path modeling for the filtered-X LMS algorithm is proposed for the active control of periodic noise. Previous noninvasive algorithms have utilized iterative search methods that have proven unsuccessful in delivering sufficiently accurate secondary path models for use by the filtered-X LMS-based control system, especially in time-varying systems, resulting in poor performance and instability. The proposed method, based in the frequency domain, uses the concept of linear independence of two equations/two unknowns to arrive at the secondary path estimate. Linear independence of the two equations is achieved by adjusting the control filter output via the filter coefficients prior to the acquisition of the second set of data corresponding to the second equation.; The proposed method is tested on a unique “sound-free” system designed and built specifically for the validation of active noise control algorithms. A summing junction circuit simulates the interference between the primary and secondary disturbances while a computer housing a manually adjustable filter provides a time-varying secondary path; signal generators provide the reference signal. Sinusoidal and dual-frequency signals are used to validate the proposed method. In order to demonstrate the ability of the proposed secondary path modeler to track system changes, tests are conducted where the frequencies are shifted and also where the secondary path is evolving. The secondary path estimates are then compared to the correct estimates ascertained using an LMS-based adaptive filter. The results reflect a simple and elegant secondary path modeling algorithm that provides estimates of unprecedented accuracy for time-varying systems. This accuracy in turn allows for stable operation of the filtered-X LMS-based control filter and thus reliable noise cancellation performance.