scholarly journals Artificial intelligent techniques based on direct torque control of induction machines

Author(s):  
Mona Magdy ◽  
Salama Abu-Zaid ◽  
Mahmoud A. Elwany

The direct torque control (DTC) system, which is based on induction machine drive is a developed and simple control method. It allows high dynamic performance with very simple hysteresis control scheme; However, its disadvantages are high current, torque, and flux ripple. In this paper, DTC of induction machine drive has been improved by using the applications of artificial intelligence (AI) approaches to reduce the current, torque, and flux ripples and also get better performance of the machines. At the conclusion of this study, the outcomes of traditional DTC and artificial intelligent methods are compared. By the program MATLAB/SIMULINK, the modeling and simulation results of the DTC system for induction machine (IM) have been proposed.

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 820 ◽  
Author(s):  
Ibrahim Mohd Alsofyani ◽  
Kyo-Beum Lee

Constant-frequency torque regulator–based direct torque control (CFTR-DTC) provides an attractive and powerful control strategy for induction and permanent-magnet motors. However, this scheme has two major issues: A sector-flux droop at low speed and poor torque dynamic performance. To improve the performance of this control method, interleaving triangular carriers are used to replace the single carrier in the CFTR controller to increase the duty voltage cycles and reduce the flux droop. However, this method causes an increase in the motor torque ripple. Hence, in this work, different discrete steps when generating the interleaving carriers in CFTR-DTC of an induction machine are compared. The comparison involves the investigation of the torque dynamic performance and torque and stator flux ripples. The effectiveness of the proposed CFTR-DTC with various discrete interleaving-carriers is validated through simulation and experimental results.


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