DocumentCode :
2702546
Title :
A neural network-based direct inverse control for active control of vibrations of mechanical systems
Author :
De Abreu, Gustavo Liuz C M ; Teixeira, Rafael Luís ; Ribeiro, José F.
Author_Institution :
Lab. de Dinamica de Sistemas Mecanicos, Univ. Fed. de Uberlandia, Brazil
fYear :
2000
fDate :
2000
Firstpage :
107
Lastpage :
112
Abstract :
This paper describes the use of artificial neural networks for the control of vibrations of a mechanical system using its experimental direct inverse model. The neural controller is trained to model the experimental inverse model of the plant using the backpropagation algorithm with simulated annealing. The inverse model of the plant is obtained by the training mechanism that uses experimental input and output data. After the training, the neural network is used as a forward controller. The efficiency and the robustness of the controller are shown through experimental tests. The neural control algorithm is implemented in a computer and the performance of controller is evaluated under a set of experimental tests made to the active control of vibrations of a mechanical system of one degree of freedom actuated by magnetic actuators
Keywords :
backpropagation; neurocontrollers; simulated annealing; stability; vibration control; backpropagation; magnetic actuators; mechanical system; neural networks; neurocontrol; robustness; simulated annealing; vibration control; Artificial neural networks; Backpropagation algorithms; Control systems; Inverse problems; Mechanical systems; Neural networks; Robust control; Simulated annealing; Testing; Vibration control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2000. Proceedings. Sixth Brazilian Symposium on
Conference_Location :
Rio de Janeiro, RJ
ISSN :
1522-4899
Print_ISBN :
0-7695-0856-1
Type :
conf
DOI :
10.1109/SBRN.2000.889722
Filename :
889722
Link To Document :
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