document: Experimental investigation of active vibration control using neural networks and piezoelectric actuators The use of neural networks for identification and control of smart structures is investigated experimentally . Piezoelectric actuators are employed to suppress the vibrations of a cantilevered plate subject to impulse , sine wave and band-limited white noise disturbances . The neural networks used are multilayer perceptrons trained with error backpropagation . Validation studies show that the identifier predicts the system dynamics accurately . The controller is trained adaptively with the help of the neural identifier . Experimental results demonstrate excellent closed-loop performance and robustness of the neurocontroller
doc_bio_tags: O O O B I I O B I O B I O O O B I O B O B O B I O O O O B I O O O O O O O O B I O O O O O O O O B I I O O B I O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B
extractive_keyphrases: active vibration control neural networks piezoelectric actuators identification control smart structures cantilevered plate white noise disturbances multilayer perceptrons error backpropagation robustness neurocontroller
abstractive_keyphrases: closed-loop performance vibration suppression