Title :
A neuro-fuzzy-based on-line efficiency optimization control of a stator flux-oriented direct vector-controlled induction motor drive
Author :
Bose, Bimal K. ; Patel, Nitin R. ; Rajashekara, Kaushik
Author_Institution :
Dept. of Electr. Eng., Tennessee Univ., Knoxville, TN, USA
fDate :
4/1/1997 12:00:00 AM
Abstract :
Fuzzy logic-based online efficiency optimization control has been described previously for an indirect vector-controlled induction motor drive. The purpose of this paper is to extend the same control to a stator flux-oriented electric vehicle induction motor drive and then implement the fuzzy controller by a dynamic back propagation neural network-based controller. The principal advantage of fuzzy control, i.e., fast convergence with adaptive step size of the control variable, is retained. The neural network adds the advantage of fast control implementation, either by a dedicated hardware chip or by digital signal processor (DSP)-based software
Keywords :
backpropagation; control system synthesis; electric propulsion; electric vehicles; fuzzy control; induction motor drives; machine control; machine theory; neurocontrollers; optimal control; stators; traction motor drives; DSP-based software; adaptive step size; convergence; direct vector control; dynamic backpropagation neural network; electric vehicle; induction motor drive; neuro-fuzzy control; online efficiency optimization control; stator flux-oriented control; Convergence; Electric variables control; Electric vehicles; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Induction motor drives; Neural networks; Stators; Vehicle dynamics;
Journal_Title :
Industrial Electronics, IEEE Transactions on