Design of Neural Network Controllers for High Efficiency Induction Motor Vector Control System
| Autor: | Wen-Shyong Lee, 李文雄 |
|---|---|
| Rok vydání: | 2005 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 93 In general, applying traditional artificial neural network structure to control systems requires off-line learning and training to obtain the optimal parameters. However, it is not easy to get suitable training data and as a result the performance of response of designed control system is not as expected in such circumstances. Therefore,to improve the drawbacks of on-line learning and adaptation properties under the traditional Artificial Neural Network architecture, this paper adopts the projection algorithm in adaptive theory to the Neural Network and a so-called Neural Network PI Controller(NNPIC) is designed to construct a new Neural Network with online learning ability, which can properly reflect dynamical characteristics of the control system and hence provide the adaptation ability and robustness. Based on the projection algorithm, this paper also proposes the Neural Network speed controller, which is combined with the Adaptive Pseudo-Reduced-Order Flux Observer, for the sensorless of Induction Motor Vector Control System.Accommodating with the high power efficiency control algorithm,the controller increases the motor operation efficiency, and gains the advantages of superior dynamical property and power-saving. From the experimental results, the speed sensorless adaptive vector control systems with the proposed Artificial Neural Network Controller shows excellent performance in both transient and steady-state responses. In addition, the Adaptive Flux Observer and rotor resistance estimator still keep the desired speed responses and robustness within the +-20% variation range of parameters. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|