DocumentCode
406153
Title
Recurrent neural networks control of dynamic systems with unknown input hysteresis
Author
Wang, Xing-Song ; Li, Li ; Su, Chun-Yi ; Hong, Heniy
Author_Institution
Dept. of Mech. Eng., Southeast Univ., Nanjing, China
Volume
1
fYear
2003
fDate
14-17 Dec. 2003
Firstpage
297
Abstract
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.
Keywords
control system synthesis; difference equations; hysteresis; neurocontrollers; recurrent neural nets; time-varying systems; differential equation; dynamic systems; input hysteresis; recurrent neural networks control; Control systems; Differential equations; Hysteresis; Intelligent actuators; Intelligent structures; Magnetic materials; Mechanical engineering; Nonlinear dynamical systems; Recurrent neural networks; Trajectory;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location
Nanjing
Print_ISBN
0-7803-7702-8
Type
conf
DOI
10.1109/ICNNSP.2003.1279269
Filename
1279269
Link To Document