Fuzzy neural network multi-modal vibration control of thin cylindrical shells laminated with photostrictive actuators

In this paper, the multi-modal vibration control of a simply supported thin cylindrical shell laminated with photostrictive actuators is studied. First, the photo-electric/shell coupling equations of a cylindrical shell laminated with the multi-layer actuator configuration are presented. Moreover, in view of the nonlinear and time-variant characteristics of photostrictive actuators, a fuzzy neural network (FNN) controller with adaptive learning rates is developed to attenuate multi-mode vibration of photo-electric laminated thin cylindrical shells. This approach has learning ability for responding to the time-varying characteristic of the multi-mode vibration induced by disturbance. Its control rule bank can be established and modified continuously by on-line learning. Finally, numerical simulation results are provided to show that the proposed intelligent controller could effectively suppress multi-mode vibration of photo-electric laminated thin cylindrical shells.