Nooradzianie Muhammad Zin

Neural network SVPWM-DTC of induction motor for EV load model

A three phases induction motor is used as an electric vehicle propulsion system in this paper. The proposed neural network speed controller is design based on the space vector modulation technique on direct torque control. Since the electric drive performance significantly lean against on the design of speed controller, thus the improvement on the speed controller become the core of this research and so it is enhanced by replace the generic speed controller by the adaptive neural network controller. The performance of the control system in addition with the neural network learning scheme are depict in this paper. The complete schemes of both conventional and proposed scheme are simulated using Mathlab. The comparison system performance between the conventional direct torque control and the proposed intelligent neural network speed control have been investigated and show a satisfy result in both steady state and transient response. The simulation results verify that the proposed direct torque controller with the adaptive speed controller for induction motor satisfy and effectiveness enough as the candidate for electric vehicle propulsion.

Fuzzy Logic Control Design for Induction Motor Speed Control Improvement Through Field Oriented Control

This paper focuses on improving induction motor performance by controlling its speed. The induction motor speed is controlled using field oriented control based structure associated with an induction motor. The field oriented control is implemented by combining with fuzzy logic control to reduce the uncertainties factors. The fuzzy logic control is developed based on Mamdani method. The inputs of fuzzy logic control are the error and derivative error between actual and reference speed of induction motor. The output of fuzzy logic control is the reference electric torque. The fuzzy logic control input output variables membership functions are chosen based on the parameters of the motor model. Motor state variables are identified indirect from induction motor model. The controller develops is implemented MATLAB Simulink. The simulation result shows that the fuzzy logic control is a suitable controller for improving induction motor performance with gives less settling time and steady state error than Proportional Integral Derivative control.