Analysis of Three Phase Induction Motor Settings To Load Changes Using Artificial Neural Networks

Abstract

benefits of induction motors in the industrial world today are numerous. This is because this induction motor has many advantages such as strong and simple construction and is cheaper to maintain. However, there are weaknesses in regulating speed and torque. One of the 3-phase induction motor speed regulation is vector control. This method is connected to a PID controller to control the input and output to reach the expected value. However, with the development of an increasingly modern era, it can now be done automatically, especially in regulating PID control, in this experiment, it wants to be done using an artificial neural network controller to be able to study the data that has been done by the PID controller to find out the input and output expected by the system so that the speed control on the induction motor runs stably. this method is able to control the speed to remain stable even though the load changes. In this study, loading tests will be carried out at 0 Nm, 80 Nm, 140 Nm, 290 Nm and 400 Nm and reference speeds of 40 rps, 75 rps and 120 rps.  The simulation results of using the artificial neural network controller show that the system can reach the expected reference speed in less than 3 ms and the average steady state error is 0.5241%.