Name
Title | ||
|---|---|---|
Precision control of magnetostrictive actuator using dynamic recurrent neural network with hysteron |
Abstract | ||
|---|---|---|
A control strategy for precision position tracking of the magnetostrictive actuator (MA) with dominant hysteresis is proposed. In this strategy, a dynamic recurrent neural network with hysteron (DRNNH) is adopted as a feedforward controller for on-line learning the inverse model of the MA to remove the effect of the hysteresis of the MA. A proportional-plus-derivative (PD) feedback controller is used to reduce the position tracking error. Simulation results validate the excellent performances of the control strategy. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11538059_80 | ICIC (1) |
Keywords | Field | DocType |
excellent performance,feedback controller,magnetostrictive actuator,inverse model,dynamic recurrent neural network,dominant hysteresis,feedforward controller,precision control,precision position tracking,position tracking error,control strategy,inverse modeling,neural network | Control theory,Control theory,Computer science,Hysteresis,Recurrent neural network,Magnetostriction,Artificial neural network,Tracking error,Actuator,Feed forward | Conference |
Volume | ISSN | ISBN |
3644 | 0302-9743 | 3-540-28226-2 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuying Cao | 1 | 3 | 1.12 |
| Jiaju Zheng | 2 | 3 | 1.12 |
| Wenmei Huang | 3 | 3 | 1.80 |
| Ling Weng | 4 | 0 | 1.35 |
| Bowen Wang | 5 | 37 | 18.85 |
| Qingxin Yang | 6 | 4 | 2.84 |