A Novel Adaptive Scheme to Improve the Performance of Feedforward Active Vibration Control Systems

Feedforward active vibration control techniques aim at canceling vibrations occurring in a system by means of introducing intentional forces that generate destructively interfering vibrations. These forces are typically controlled using an adaptive filtering algorithm that tracks the system state in real time and seeks to minimize overall vibration. One important often-overlooked issue in such systems is related with the vibrations introduced by the adaptive control algorithm itself either during its transient learning phase or due to its nonideal characteristic. These vibrations may become very significant in several mechanical structures due to resonance phenomena. In this context, this work is dedicated to the development of an effective scheme for feedforward active vibration control that is capable of dealing with undesirable vibrations introduced by the adaptive controller. A particular version of the filtered-x normalized least-mean-squares algorithm tailored to the proposed scheme is also developed. Results obtained from numerical simulation as well as from an experimental device are presented, aiming to demonstrate the effectiveness of the proposed scheme.