NDLI: A shaft sensorless control for PMSM using direct neural network adaptive observer

Content Provider	IEEE Xplore Digital Library
Author	Guo Qingding Luo Ruifu Wang Limei
Copyright Year	1996
Description	Author affiliation: Dept. of Electr. Eng., Shenyang Polytech. Univ., China (Guo Qingding)
Abstract	Rotor position detection is necessary for phase commutation and current control in high-performance PMSM. The traditional detecting method is based on resolver, absolute encoder etc. This paper presents a position and velocity sensorless control algorithm based on a direct neural model reference adaptive observer. The proposed observer comprise two neural networks which are trained to learn the electrical and mechanical model respectively. Adaptation is realized by online training using current prediction error. Various advantages of this estimating scheme over other sensorless control schemes, such as robustness, nonlinear adaptation and learning ability is shown by extensive simulations.
Starting Page	1729
Ending Page	1734
File Size	441907
Page Count	6
File Format	PDF
ISBN	0780327756
DOI	10.1109/IECON.1996.570679
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-08-09
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shafts Sensorless control Neural networks Adaptive systems Programmable control Adaptive control Multi-layer neural network Artificial neural networks Synchronous motors Rotors
Content Type	Text
Resource Type	Article

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A shaft sensorless control for PMSM using direct neural network adaptive observer