International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol 10, No 2: June 2019

DTC hybrid by different techniques of observation with Artificial Neuronal Network (ANN) for induction machine drives

Dris Ahmed (ENP University)
Mokhtar Bendjebbar (University of Technology and Science USTO)
Aek Belaidi (ENP University)



Article Info

Publish Date
01 Jun 2019

Abstract

In this article, we present the construction of observers of rotor flux and mechanical speed needed for robust control of the induction machine. Two observers will be developed for comparison. The first is based on the techniques MRAS and the second is observer of KUBOTA, with the enhanced DTC-ANN (by artificial intelligence), "sensorless DTC-ANN". The validity of the proposed methods is confirmed by the simulation results. Through this comparative study we examine each observer in terms of characteristics that distinguish him from the other through these estimated value and error of estimation (flux and the speed of rotation) on the one hand, and on the other hand we study a property of great importance in the control and the response and robustness of the observer for very low speeds.In my work I concentrate this on the observer of KUBOTA because I noticed that during my research in the previous research and research there is very little and no detail even in terms of mathematical model in addition to the form of comparative study between him and the observer of MRAS in terms of the principle of control, accuracy, sensitivity and special response to low speeds and error In observation.The THD (Total Harmonic Distortion) of stator current, torque ripple and stator flux ripple are determined and compared with conventional DTC control scheme using Matlab/Simulink environment.

Copyrights © 2019






Journal Info

Abbrev

IJPEDS

Publisher

Subject

Control & Systems Engineering Electrical & Electronics Engineering

Description

International Journal of Power Electronics and Drive Systems (IJPEDS, ISSN: 2088-8694, a SCOPUS indexed Journal) is the official publication of the Institute of Advanced Engineering and Science (IAES). The scope of the journal includes all issues in the field of Power Electronics and drive systems. ...