Subband reinforced adaptive feedback control algorithm in mechanical vibration control

In mechanical vibration control, the conventional least mean square (LMS)-based adaptive feedback control algorithm can hardly lead to a satisfying suppression of tonal vibrations when the disturbance is composed of multiple harmonics. The convergence rate of the conventional LMS-based adaptive feedback algorithm is analyzed, and it is revealed that the convergence rate is significantly affected by the magnitude product of the control channel and the disturbance. The smaller the magnitude product, the slower the convergence speed. Based on this analysis, a subband reinforced adaptive feedback control algorithm is proposed to increase the convergence rate in the frequency band of weak controllability. In this algorithm, the components of slow convergence rate are first extracted from the error signal with subband filters and then controlled independently to achieve fast attenuation. The role of these subband filters is to increase the magnitude product of associated components. Numerical and experimental results have shown that the reinforced adaptive control algorithm is effective and the tonal components, including those of weak controllability, are suppressed almost in the whole frequency range. The proposed algorithm can achieve better vibration attenuation than the conventional LMS-based adaptive feedback algorithm when the disturbance contains multiple harmonics.