Sensorless backstepping control using a Luenberger observer for double-star induction motor

• Autorzy: Chaabane Hadji , Eddine Khodja Djalal , Salim Chakroune

Identyfikatory

DOI

10.24425/aee.2020.131761

• Języki publikacji: EN

Abstrakty

EN

In this paper, we propose sensorless backstepping control of a double-star induction machine (DSIM). First, the backstepping approach is designed to steer the flux and speed variables to their references and to compensate uncertainties. Lyapunov”s theory is used and it demonstrates that the dynamic tracking of trajectories tracking is asymptotically stable. Second, unfortunately, this law control called sophisticated is a major problem which leads to the necessity of using a mechanical sensor (speed, load torque). This imposes an additional cost and increases the complexity of the montage. In practice, this variable is unknown and its measurement is expensive. To restrain this problem we estimate speed and load torque by using a Luenberger observer (LO). Simulation results are provided to illustrate the performance of the proposed approach in high and low variable speeds and load torque disturbance.

Słowa kluczowe

EN

backstepping control; double star induction machine (DSIM) drive; Luenberger observer

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2020
• Tom: Vol. 69, nr 1
• Strony: 101--116
• Opis fizyczny: Bibliogr. 22 poz., rys., tab., wz.

Twórcy

autor

Chaabane Hadji

• Research Laboratory of Electrical Engeneering, University of M’sila BP 166, Ichbilia 28000, Algeria

autor

Eddine Khodja Djalal

• Research Laboratory of Electrical Engeneering, University of M’sila BP 166, Ichbilia 28000, Algeria
• Signals & Systems Laboratory, Institute of Electrical and Electronic Engineering Boumerdes, Algeria

autor

Salim Chakroune

• Research Laboratory of Electrical Engeneering, University of M’sila BP 166, Ichbilia 28000, Algeria

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).