Prediction of Time-Delay Neural Network Modeling for First Order Control System

This study explores the use of neural networks to predict the parameters of a first-order time-delay system based on its response to a step input. A feed forward neural network architecture is proposed to estimate the gain, time constant, and time delay, which are traditionally difficult to obtain through classical methods. The model accurately estimates system parameters, with minimal deviation between the original and predicted responses. This approach offers a robust framework for parameter estimation in time-delay systems and holds potential for broader applications in system control.