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Speed sensorless vector control of doubly fed induction machine using fuzzy logic control equipped with Luenberger observer

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Abstract

This paper proposes a novel sensorless and sensor-based speed control of a doubly fed induction machine (DFIM). The proposed methodology consists of using the principle of rotor flux-oriented control (RFOC) to eliminate the cross-coupling that occurs between the rotor flux and the electromagnetic torque of the DFIM system. For the sensor-based mechanical speed control case, a robust fuzzy logic controller (FLC) is synthesized. For the sensorless speed control case, the Luenberger observer is proposed to optimally estimate the unknown mechanical speed, which is then employed in the FLC synthesis. The control methodology including the RFOC principle and the FLC synthesis equipped with the Luenberger observer is therefore the main contribution of this paper. Typically, the closed-loop system is simulated by a single pulse-width modulated (PWM) inverter, which is linked to the DFIM system's rotor, where the corresponding rotational speed is often controlled using a conventional proportional–integral (PI) controller. The controller parameters are accordingly tuned from the datasheet describing the machine using guideline-based tuning rules, available in conventional synthesis methods. Unfortunately, such tuning requires rigorous computational time and extensive prior knowledge of DFIM parameter set. To overcome this drawback, the speed control based on the existing conventional PI controller is replaced by the one based on the proposed robust FLC for speed control with sensor and the proposed FLC equipped with Luenberger observer for the sensorless speed control. The simulation results show the superiority of the proposed control strategy over the one provided by the conventional PI controller-based RFOC strategy, in terms of reference tracking dynamic and closed-loop robustness against inappropriate DFIM model parameters.

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Data availability

All data and code is available with an open source from https://github.com/yousfi26/Matlab-Simulink-codes.

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Acknowledgements

The authors would like to thank Dr. Boulsina Fayçal for his significant comments that enhanced the current paper.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Larbi Tebessi University, Tebessa, Algeria

    Laatra Yousfi & Sakina Aoun

  2. Laboratoires des Télécommunications LT, University 8 May 1945 of Guelma, Guelma, Algeria

    Moussa Sedraoui

Authors
  1. Laatra Yousfi
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  2. Sakina Aoun
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  3. Moussa Sedraoui
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Contributions

Yousfi Laatra, Aoun Sakina, and Sedraoui Moussa contributed equally to the preparation of this manuscript.

Corresponding author

Correspondence to Laatra Yousfi.

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The authors reported no potential conflict of interest.

Appendix

Appendix

See Tables 2 and 3.

Table 2 Meaning and value of each DFIM parameter used in simulation part
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Table 3 PI parameters and the observer gain parameters
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MATLAB/SIMULINK block diagrams used in simulation (Figs.

Fig. 18
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Simulink model of DFIM with indirect RFOC and Luenberger observer

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Fig. 19
figure 19

Simulink model of indirect RFOC subsystem

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19).

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Yousfi, L., Aoun, S. & Sedraoui, M. Speed sensorless vector control of doubly fed induction machine using fuzzy logic control equipped with Luenberger observer. Int. J. Dynam. Control 10, 1876–1888 (2022). https://doi.org/10.1007/s40435-022-00946-0

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  • DOI: https://doi.org/10.1007/s40435-022-00946-0

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