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Recurrent neural networks control of dynamic systems with unknown input hysteresis

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4 Author(s)
Xing-Song Wang ; Dept. of Mech. Eng., Southeast Univ., Nanjing, China ; Li Li ; Chun-Yi Su ; Hong, H.

This paper deals with the control of dynamic systems preceded by an unknown hysteresis, where the hysteresis is modeled by a differential equation. By exploiting properties of the differential equation, a recurrent neural network is developed to construct a hysteresis inverse, which can compensate the affection of the input hysteresis. By using a traditional PD controller, the whole system tracks a desired trajectory within a specified precision. Simulation results verified the proposed schemes.

Published in:
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on  (Volume:1 )

Date of Conference: 14-17 Dec. 2003

Page(s):
297 - 300 Vol.1
Print ISBN:
0-7803-7702-8
INSPEC Accession Number:
8055889
Conference Location :
Nanjing
Digital Object Identifier :
10.1109/ICNNSP.2003.1279269
Product Type:
Conference Publications

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