Original scientific paper
https://doi.org/10.7305/automatika.2016.10.1345
Optimized Torque Control via Backstepping Using Genetic Algorithm of Induction Motor
Souad Chaouch
; Laboratory of Electromagnetic Induction and Propulsion Systems University of Batna, Route de Biskra, Batna, 05000, Algeria
Latifa Abdou
; Laboratory of Identification, Control, Command and communication LI3cub. University of Biskra
Said Drid
; Laboratory of Electromagnetic Induction and Propulsion Systems University of Batna, Route de Biskra, Batna, 05000, Algeria
Larbi Chrifi-Alaoui
; GEII Department, University of Picardie Jules Verne, 13 François Mitterand avenue, Cuffies, 02280 France
Abstract
This paper proposes a novel hybrid control of induction motor, based on the combination of the direct torque control DTC and the backstepping one, optimized by Genetic Algorithm (GA). First the basic evolution of DTC is explained, where the torque and stator flux are controlled by non linear hysteresis controllers which cause large ripple in motor torque at steady state operation. A Backstepping control is applied to overcome these problems, however the used parameters are often chosen arbitrarily, which may affect the controller quality. To find the best parameters, an optimization technique based on genetic algorithm is used. Also, in order to obtain accurate information about stator flux, torque and load torque, open loops estimators are used for this Backstepping control. At last, experimental results are presented in order to prove the efficiency of the above mentioned control technique.
Keywords
Induction motor; Bachstepping Control; DTC; Genetic Algorithms
Hrčak ID:
179410
URI
Publication date:
25.1.2017.
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