Speed Control Under Load Uncertainty of Induction Motor Using Neural Network Auto-Tuning PID Controller

Abstract

Induction motor has been an important machine in many applications especially in Electric Vehicles(EVs), The improve in performance of the induction motor will result in a more stable and efficient drive system of the EV which will be beneficial for future applications which was achieved through the introduction of Variable-Speed Drive system. However, in this non ideal world, uncertainty must be considered. Load of induction motor has high uncertainty which cause a high degree of instability or degradation in performance of the system. In order to keep induction motor in control to uncertainty of load, a suitable controller should be introduced to solve the problem. Neural Network Controllers are used widely in non-linear system due to its adaptivity to new conditions as the controller uses a learning system from past inputs and outputs. This study is to apply neural network in auto-tuning PID controller for improving the accuracy of induction motor drive in electrical vehicles when load is uncertain. The final objective is to improve, through the addition of neural network, the robustness and performance of the induction motor.