Position Control of Separately Excited DC Motor Using NARMA-L2 Neural Network Controller

Abstract Due to the widespread use of dc motors, their position or speed control becomes very important. The aim in this paper is providing a new method for intelligent position control of separately excited dc motor using neural networks. For this purpose the NARMA-L2 neural network controller is used. In the position control using neural network, based position for neural network intended as input position (ideal), and after adapting of output position of motor to base position, Armature voltage become zero and motor stops working. In this way, neural network learns the used model of dc motors to control the position, then the input optimized for matching of model output position to ideal position. Advantage of the proposed neural network method is, correction coefficients during the working engine and Replies robustness to changes inertia moment (J) and friction (B). Unlike the PID controllers that will lose their optimization Performance with changing one of the model parameters, such as J & B ,and need to reset the parameters of the controller, the proposed method needs not to redesign, and these parameters repair automatically. Proposed method is simulated using information from a separately excited dc motor in SIMULINK environment of MATLAB software. Results show that by using of proposed method, fluctuations in response and need times to reach the ideal situation decreases.