ARTIFICIAL NEURAL NETWORK MODEL: A TOOL FOR INTELLIGENT CONTROL SYSTEM

Abstract

This research focused on the application of Artificial Neural Networks (ANN) for controlling the speed of a DC motor. It delved into the intricacies of ANN, encompassing the fundamental aspects of learning, training, and model development within this neural network paradigm. To achieve the goals of this research, an Artificial Neural Network (ANN) model controller for a DC motor alongside a conventional PID controller were developed.  Simulations of both models were conducted and their results were compared to assess potential improvements. The simulations clearly demonstrated that the ANN controller exhibits greater stability compared to the PID controller. In terms of performance, when comparing the percentage error of the speed control of the DC motor, the PID controller had a deviation of 1.46%, whereas the ANN model displayed a significantly improved deviation of only 0.24%. In conclusion, the percentage improvement established from comparing the results of the conventional PID and the Proposed ANN model demonstrated that the ANN model outperformed the existing PID model, offering superior results.