DocumentCode :
3666876
Title :
BP neural network MRAC applied to slip gain adjusting
Author :
Qing Ku;Gengguo Cheng;Yun Wang
Author_Institution :
Institute of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China
fYear :
2015
fDate :
6/1/2015 12:00:00 AM
Firstpage :
1676
Lastpage :
1680
Abstract :
Asynchronous machine with indirect vector control is very popular in industrial applications. However, it is sensitive to rotor slip gain. In this paper, model reference adaptive system combined with PI controller based on BP neural network, then Electromagnetic torque of asynchronous motor could be online estimated by model reference adaptive system, BP neural network controller could adaptively adjust the parameters according to the error between the reference model and adaptive model, then steady-state and dynamic performance of the system could achieve good performance. Basic principles and schematic diagram are described. Simulation and experiment results confirm the validity of the proposed method.
Keywords :
"Adaptation models","Rotors","Machine vector control","Mathematical model","Torque","Neural networks","Stators"
Publisher :
ieee
Conference_Titel :
Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8728-3
Type :
conf
DOI :
10.1109/CYBER.2015.7288198
Filename :
7288198
Link To Document :
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