Fuzzy Speed Control of Induction Motor with Five-Level DTCBased Neural Networks

Abstract

Direct Torque Control (DTC) is a control technique in AC drive systems to obtain highperformance torque control. In this paper, the Author presents the induction motor speed control with five-level DTC. This paper proposes to replace the selector switches statements of the voltage inverter by a selector based on Artificial Neural Network (ANN), which is able to manage in the same way the switches states, without resorting to complex programming. The speed loop regulation is carried out by a fuzzy controller giving the exceeding performance in comparison with a classic PI controller. The performance of the DTC-Artificial Neural Network (DTC-ANN) & DTC-ANN with the fuzzy PI controller is tested through Matlab/Simulink. The simulation results, which illustrate the performance of the proposed control scheme in comparison with the DTCANN scheme are given.

Keywords:

DTC, Induction motor, Fuzzy PI controller, Artificial neural network, Fivelevel.