A neuro-fuzzy-based on-line efficiency optimization control of a stator flux-oriented direct vector-controlled induction motor drive

Fuzzy logic-based on-line efficiency optimization control has been described in the literature [1] 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.