Analog Implementation and Realization of Artificial Neural Network Using Electronic Devices
Majli Nema Hawas1, Baker K. Al Rekaby2
1Majli Nema Hawas, Department of Computer Engineering, College of Electric. & Electro. Engineering, Baghdad, Iraq
2Baker K. Al Rekaby, Department of Computer Engineering, College of Electric. & Electro. Engineering, Baghdad, Iraq
Manuscript received on March 01, 2015. | Revised Version Manuscript Received on March 23, 2015. | Manuscript published on March 20, 2015. | PP: 5-7 | Volume-1 Issue-5, April 2015
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper introduces the implementation and realization of Artificial Neural Network (ANN) application in control systems such as real time speed control of permanent magnet DC motor. Two methods of ANN technique has been used, first a multi-layer feed forward neural network, second nonlinear auto regressive moving average based neural network (NARMA-L2) in order to overcome the problems associated with conventional control methods such as PI (Proportional-Integral).The two controller have been train offline and run online in real time using MATLAB software environment and data acquisition card as interface between a personal computer and the system.
Keywords: ANN ; NARMA-L2;PMDC motor; Real time control system.