Speed Estimators Using Stator Resistance Adaptation for Sensorless Induction Motor Drive

Hau Huu Vo, Pavel Brandstetter, Chau Si Thien Dong, Thinh Cong Tran

Speed Estimators Using Stator Resistance Adaptation for Sensorless Induction Motor Drive

Číslo: 3/2016
Periodikum: Advances in Electrical and Electronic Engineering
DOI: 10.15598/aeee.v14i3.1732

Klíčová slova: Artificial neural network; induction motor drive; model reference adaptive system; sensorless control, Umělá neuronová síť; Indukční pohon motoru; Model referenčně adaptivního systém; Bezsenzorové ovládání

Pro získání musíte mít účet v Citace PRO.

Přečíst po přihlášení

Anotace: The paper describes speed estimators for a speed sensorless induction motor drive with the direct torque and flux control. However, the accuracy of the direct torque control depends on the correct information of the stator resistance, because its value varies with working conditions of the induction motor. Hence, a stator resistance adaptation is necessary. Two techniques were developed for solving this problem: model reference adaptive system based scheme and artificial neural network based scheme. At first, the sensorless control structures of the induction motor drive were implemented in Matlab-Simulink environment. Then, a comparison is done by evaluating the rotor speed difference. The simulation results confirm that speed estimators and adaptation techniques are simple to simulate and experiment. By comparison of both speed estimators and both adaptation techniques, the current based model reference adaptive system estimator with the artificial neural network based adaptation technique gives higher accuracy of the speed estimation.