Hybrid Vibration Control under Broadband Excitation and Variable Temperature Using Viscoelastic Neutralizer and Adaptive Feedforward Approach

Abstract

Vibratory phenomena have always surrounded human life. The need for more knowledge and domain of such phenomena increases more and more, especially in the modern society where the human-machine integration becomes closer day after day. In that context, this work deals with the development and practical implementation of a hybrid (passive-active/adaptive) vibration control system over a metallic beam excited by a broadband signal and under variable temperature, between 5 and 35°C. Since temperature variations affect directly and considerably the performance of the passive control system, composed of a viscoelastic dynamic vibration neutralizer (also called a viscoelastic dynamic vibration absorber), the associative strategy of using an active-adaptive vibration control system (based on a feedforward approach with the use of the FXLMS algorithm) working together with the passive one has shown to be a good option to compensate the neutralizer loss of performance and generally maintain the extended overall level of vibration control. As an additional gain, the association of both vibration control systems (passive and active-adaptive) has improved the attenuation of vibration levels. Some key steps matured over years of research on this experimental setup are presented in this paper.

On the use of viscoelastic materials characterized by Bayesian inference in vibration control

“…From a detailed knowledge of the dynamic behavior of viscoelastic materials, the implementation of effective control designs becomes possible. In view of the absence or presence of an external power source, vibration control systems can be divided into passive and active control techniques (Marra et al, 2016;Inman, 2017). Among the passive control techniques using viscoelastic materials, one can mention the introduction of damping, the addition of viscoelastic links, the insertion of auxiliary devices known as viscoelastic dynamic neutralizers, and the implementation of isolation systems.…”

Error Signal Differential Term Feedback Enhanced Variable Step Size FxLMS Algorithm for Piezoelectric Active Vibration Control

“…e weight coefficients of the adaptive controller are adjusted according to the adaptive algorithm that usually is LMS algorithm, so that the mean square value of the vibration response measured by sensor converges to the minimum direction. e developed FxLMS vibration control algorithm has advantages of good convergence and strong adaptability, and does not depend on the accurate model of controlled structure, which has become one of the hotspots of AVC algorithm research [2][3][4][5]. However, in the FxLMS control algorithm, the convergence rate and steadystate error of LMS algorithm are greatly affected by the step size μ.…”