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

Content Provider	IEEE Xplore Digital Library
Author	Shufang Wang Jun Li Yinan Li Zhiyong Yang
Copyright Year	2010
Description	Author affiliation: School of Mechanical Electronic, Beijing Union University, China (Shufang Wang; Jun Li; Yinan Li) \|\| Astronautics Long March rocket technology Limiting Company, Beijing, China (Zhiyong Yang)
Abstract	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.
File Size	691436
File Format	PDF
ISBN	9781424463671
e-ISBN	9781424463701
DOI	10.1109/ICETC.2010.5529733
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	self-learning fuzzy logic Induction motors Torque Rotors Hysteresis motors Servo motor Induction motor drives Fuzzy logic velocity observer DTC Velocity control Stators Servomechanisms Servomotors
Content Type	Text
Resource Type	Article

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