DocumentCode :
2837706
Title :
Vector control of induction motor using a hybrid neural network/fuzzy logic model
Author :
Ping, Hew Wooi ; Rahim, Nasarudin Abd
Author_Institution :
Malaya Univ., Kuala Lumpur, Malaysia
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
109
Abstract :
This paper presents the practical implementation scheme of a three-phase induction motor vector drive using a hybrid neural network/fuzzy logic control model. In vector control, the three phase currents are transformed into a single current vector rotating at synchronous speed. The transformation enabled a single control output to control current values in all the three phases thus greatly simplifying the control model. This paper incorporates a hybrid neural network/fuzzy logic model into the vector control model to make it more intelligent. The neural network/fuzzy logic model is used as a universal function approximator that transforms the user input command and the speed sensor feedback to Δlq (the change in q current quantities) and the machine synchronous speed
Keywords :
electric current control; fuzzy control; induction motor drives; machine vector control; neurocontrollers; current values control; hybrid neural network/fuzzy logic model; induction motor; single rotating current vector; speed sensor feedback; synchronous speed; three phase currents transformation; three-phase induction motor vector drive; universal function approximator; vector control; Fuzzy logic; Induction motors; Intelligent sensors; Machine vector control; Mathematical model; Multi-layer neural network; Neural networks; Neurofeedback; Rotors; Torque control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-6338-8
Type :
conf
DOI :
10.1109/ICPST.2000.900040
Filename :
900040
Link To Document :
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