Experimental study on active vibration control of a flexible cantilever using an artificial neural-network state predictor

Abstract

Active control of flexible structures is crucial for the successful operation of large aerospace structures. One of the predominant difficulties in the active control of flexible structures is that such structures have a number of vibratory modes within or beyond the bandwidth of the controller. In the active control of flexible structures, spillover can occur because only a few vibratory modes are dealt with by the control. Although modal-space-based optimal control is known to avoid spillover, it requires a large number of sensors and actuators. In this study the modified independent modal space control (MIMSC) algorithm proposed by Baz et al is adopted to minimize the number of actuators. An artificial neural network is also proposed to identify the system characteristics and to reduce the number of sensors. Experiments are performed for the active vibration control of a flexible aluminum cantilever beam employing a piezoactuator. It is experimentally found that active control with the proposed artificial neural-network state predictor is able to suppress vibration successfully without spillover.