Neural network discrimination in intelligent vibration control

The overall goal of this study lies in the multi-mode structural vibration control for systems, based on spatial information. In order to accomplish t his task, a neural network was designed to identify the shape of the domina nt vibration mode by using properly located piezoelectric sensors. The netw ork then chose a set of scaling gains for a fuzzy logic controller that had been optimally tuned for that particular mode's shape. Next, a fuzzy logic controller was employed to control the vibratory system. The novel techniq ue was experimentally verified on an aluminum cantilever beam system that w as augmented with two lead zirconate titanate (PZT) actuators and two PZT s ensors. The optimized control strategy was then compared to traditional fuz zy logic control. Finally the mass of the plant was increased by over a fac tor of 1.5 and the same controller was used to adequately stop vibration.