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DYNAMIC SYSTEM IDENTIFICATION USING TIME-DELAY FEEDFORWARD NEURAL NETWORKS: APPLICATION TO DC MOTOR | ||
| DIYALA JOURNAL OF ENGINEERING SCIENCES | ||
| Article 9, Volume 3, Issue 1, 2010, Pages 65-79 PDF (0 K) | ||
| Author | ||
| Ali Khudhair Mutlag | ||
| Abstract | ||
| The universal function approximation capabilities of multilayer feedforward neural networks make it a popular choice for modeling dynamic systems. In this paper, identification of dynamic system using time-delay feedforward neural networks with application to DC motor as a case study has been developed. The developed neural network model is a three layer network with nonlinear (sigmoid) activation functions in the hidden layer and linear output layer with input-output delays. Simulation results showed that the neural networks are promising tool for dynamic system identification. | ||
| Keywords | ||
| System Identification; neural networks; DC motor | ||
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