Self-learning fuzzy velocity observer for DTC servo induction motor drives

被引：0
|
作者：
Wang S. [1 ]
Li J. [1 ]
Li Y. [1 ]
Yang Z. [2 ]
机构：
[1] School of Mechanical Electronic, Beijing Union University, Beijing
[2] Astronautics Long March Rocket Technology, Limiting Company, Beijing
来源：
ICETC 2010 - 2010 2nd International Conference on Education Technology and Computer | 2010年 / 4卷
关键词：
DTC; Self-learning fuzzy logic; Servo motor; Velocity observer;
D O I：
10.1109/ICETC.2010.5529733
中图分类号：
学科分类号：
摘要：
In modern servo control system, velocity observer design is particularly important to achieve high accuracy. In term of conventional observer depends on motor parameters and model accuracy; it is difficult to achieve high-precision velocity and position control. Using fuzzy control algorithm, this paper researched on DTC servo induction motor control. In order to overcome subjective of fuzzy rule, a self learning fuzzy logic is suggested in detail. Moreover, a DTC induction motor servo control simulation model is established, which adopts the self-learning fuzzy velocity observer proposed. Based on it, an experimental platform included TI TMS320LF2407DSP combination with IPM is build. Experiment results show that the proposed observer can be well observed servo motor velocity. © 2010 IEEE.
引用
收藏
页码：V457 / V460
页数：3
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