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Speed control of separately excited dc motor using artificial intelligent approach

Abstract

This paper presents the ability of Artificial Intelligent Neural Network ANNs for the separately excited dc motor drives. The mathematical model of the motor and neural network algorithm is derived. The controller consists two parts which is designed to estimate of motor speed and the other is which to generate a control signal for a converter. The separately excited dc motor has some advantages compare to the others type of motors and there are some special qualities that have in ANNs and because of that, ANNs can be trained to display the nonlinear relationship that the conventional tools could not implemented such as proportional-integral-differential (PID) controller. A neural network controller with learning technique based on back propagation algorithm is developed. These two neural are training by Levenberg�Marquardt. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. The simulation results are presented to demonstrate the effectiveness and the proposed of this neural network controller produce significant improvement control performance and advantages of the control system DC motor with ANNs in comparison to the conventional controller without using ANNs

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