Nanyang Technological University, Singapore
It is my honor to be the editor-in-chief of IJEETC. The journal publishes good papers which focous on the advanced researches in the field of electrical and electronic engineering & telecommunications.
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.
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