Abstract—Artificial Neural Network has found so many applications in engineering. This paper focuses on extrapolating the speed of DC motor, given a set of input conditions. Experimental data consisting of input voltage and speed was collected from actual dc motor in the laboratory. This served as input/target pairs for the ANN after modeling and simulation of the DC Motor in Matlab Simulink. The network training was carried out using the Levenberg-Marquardt (LM) standard backpropagation algorithm because of its high speed of convergence and accuracy. The results show that the ANN model correctly maps the input to the output. This shows that Artificial Neural Network was able to predict the speed accurately.

Index Terms—DC Motors, Artificial Neural Networks, Levenberg-Marquardt standard backpropagation algorithm, and Speed Prediction

Cite: Opata Udoka C , "USING LEVENBERG-MARQUARDT STANDARD BACK-PROPAGATION ALGORITHM IN SPEED EXTRAPOLATION FOR DC MOTORS," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 5, No. 3, pp. 1-9, July 2016.