Roslina Mat Ariff

Vector Control of Induction Motor Using Neural Network

This paper deals with field oriented control of induction motor drive system with an online neural network for speed control. The field oriented control used to decoupling the flux and torque in order to get the performance as well as direct current motor. The online neural network is designed to maintain the output speed variation. To verify the effectiveness of the proposed method, a simulation model was developed. The result shows that the performance of transient response is improved in term of overshoot and settling time by using neural network field oriented control system. It is concluded that neural network based field oriented control schemes of induction motor drive is more effective to replace the conventional proportional integral derivative based field oriented control technique.

Induction Motor Drive Based Neural Network Direct Torque Control

A neural network based direct torque control of an induction motor was presented in this paper. The paper trained a neural network for speed controller of the machine to use in the feed-back loop of the control system. The description of the control system, training procedure of the neural network is given in this paper. The complete neural network based direct torque control scheme of induction motor drive is simulated using MATLAB. The acquired results compared with the conventional direct torque control reveal the effectiveness of the neural network based direct torque control schemes of induction motor drives. The proposed scheme improved the performance of transient response by reduces the overshoot. The validity of the proposed method is verified by the simulation results.

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.

Speed Control of Permanent Magnet Synchronous Motor Using FOC Neural Network

This paper presents the performance analysis of the field oriented control for a permanent magnet synchronous motor drive with a proportional-integral-derivative and artificial neural network controller in closed loop operation. The mathematical model of permanent magnet synchronous motor and artificial neural network algorithm is derived. While, the current controlled voltage source inverter feeding power to the motor is powered from space vector pulse width modulation current controlled converter. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. The simulation results prove the proposed artificial neural network controller produce significant improvement control performance compare to the proportional-integral-derivative controller for both condition controlling speed reference variations and constant load. It can conclude that by using proposed controller, the overshoot, steady state error and rise time can be reducing significantly.

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.