A neuro-fuzzy based parameter identification of an indirect vector-controlled induction motor drive

In this paper an adaptive field oriented control of induction motor drive is proposed. The adaptive scheme uses a neuro-fuzzy approach for the identification of the rotor time constant, which is used to adjust the estimate of the slip angular speed. First, a fuzzy logic estimator was developed and tuned, then the fuzzy estimator was implemented by a dynamic backpropagation neural network-based controller. The fast convergence of the fuzzy control is maintained by using adaptive step size of the control variable. The neural network implementation adds the advantage of fast computation, either by a dedicated hardware chip or by digital signal processor (DSP)-based software. Computer simulation results are obtained and the performance of the resulting field oriented controller is analyzed.