Enhanced inverse model LMS algorithm for active control of harmonic response clusters

Harmonic responses can be seen widely in many applications, such as vehicle powertrain noise, gear vibration, and other rotating machineries. Hence, to develop an effective system for harmonic control is highly desirable. For single frequency control, it can be easily suppressed by most active control systems. However, when a cluster of harmonic responses that spreads over a wide frequency range or contains rapidly varying frequencies, the traditional filtered-x least mean square (FXLMS) algorithm may not be able to achieve significant enough reduction over a wide frequency range or track variations in frequency due to the large dynamic range of secondary path in that wide spectral range. In this study, an enhanced algorithm, namely the inverse model least mean square algorithm (IMLMS), which utilizes the inverse model of the secondary path to minimize the effect of the secondary path dynamics on the algorithm convergence, is proposed to improve the convergence property and tracking ability of the active control system. Numerical simulation using synthesized signals was performed. Results show significant improvement on the convergence of the system and in turn achieving more reductions in the responses over a wide frequency range by the proposed scheme.