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
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;
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
DOI :
10.1109/ICNNSP.2003.1279269
