Smart structure with build-in sensor(s) and actuator(s) that can actively and adoptively change its physical geometry and properties has been considered one of the best candidates in vibration control applications. Implementation of neural networks to system identification and vibration suppression of a smart structure is conducted in this paper. Three neural networks are developed, one for system identification, the second for on-line state estimation, and the third for vibration suppression. It is shown both in analysis and in experiment that these neural networks can identify, estimate, and suppress the vibration of a composite structure by the embedded piezoelectric sensor and actuator. The controller is also shown to be robust to system parameter variations.

Issue Section:
Technical Papers
Topics:
Artificial neural networks, Smart structures, Vibration control, Actuators, Adaptive structures, Sensors, Vibration suppression, Composite materials, Control equipment, Geometry, State estimation, Vibration
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