Abstract
In this paper neural network is used for servo system design. It is proved that a class of nonlinear servo system can be described by its inverse dynamic model. We use open-loop and closed-loop schemes for feedforward multilayer network learning. Alopex algorithm is used to train inverse dynamic model of the plant. At the end of the paper,the design of servo system on-line control based on Feedback Error Learning is presented. Simulation results show that the method is effective in identification and control of servo system.
| Original language | English |
|---|---|
| Pages (from-to) | 60-64 |
| Number of pages | 5 |
| Journal | Xitong Fangzhen Xuebao / Journal of System Simulation |
| Volume | 10 |
| Issue number | 3 |
| Publication status | Published - 1998 |
Keywords
- Inverse system
- Neural network
- Servo system