Flux Optimization of DTC Based Induction Motor Drive Using Recurrent Neural Network

Abstract

Due to high energy conservation concern, an energy efficient electric drive becomes a challenge for researchers. Therefore, to meet this challenge, it is proposed that efficiency improvement of Direct Torque Control (DTC) based induction motor drives can be achieved by optimizing adaptive reference flux. The optimized value of flux from supply system can be obtained by using recurrent neural network (RNN). This paper focuses on optimizing the value of flux using recurrent neural network with input power as objective function. The performance of DTC based induction motor has been presented, analyzed and realized thoroughly with different training algorithms using MATLAB/Simulink®.