DocumentCode :
536184
Title :
Low speed performence improvement of sensorless IM control system based on MRAS and NN flux observers
Author :
Yi, Li ; Wenlong, Qin
Author_Institution :
Ind. Eng. Training Centre, Shanghai Univ. of Eng. Sci., Shanghai, China
Volume :
2
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
421
Lastpage :
425
Abstract :
Many electronic drivers for the induction motor control are based on sensorless technologies. This paper proposes a novel hybrid motion sensorless control system to solve the low speed problems using MRAS and NN estimation scheme which is based on rotor flux. A multilayer feedforward artificial neural network is proposed for rotor flux estimation which is more robust to noise and stator resistance variation and does not have de-drift problems which are usually associated with these adaptive schemes. A comparison between the performance of the neural network based strategy and conventional scheme is carried out. Simulation results are also presented to validate the proposed approach.
Keywords :
adaptive control; angular velocity control; induction motor drives; motion control; multilayer perceptrons; neurocontrollers; rotors; sensorless machine control; stators; MRAS flux observer; NN flux observer; dc-drift problems; electronic drivers; hybrid motion sensorless control system; induction motor control; multilayer feedforward artificial neural network; rotor flux estimation; sensorless IM control system; Artificial neural networks; Machinery; Software; Weight measurement; MRAS; neural network; speed-sensorless; vector control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658306
Filename :
5658306
Link To Document :
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