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<p>This research paper proposes a novel design of an efficient combined sliding mode observer (SMO) for induction motor flux and speed estimation. The suggested sensorless technique employs the sliding mode’s second-order approach using a model reference adaptive system (MRAS). The second-order super-twisting control method is free-chattering, which lowers the chattering effect while preserving the same good features as the first-order sliding mode control (SMC). In addition, the conjunction with the MRAS as a separated speed estimator can raise the accuracy and make the observer immune to speed fluctuations, particularly for low-speed applications. Furthermore, in order to achieve effective decoupled flux–torque control, the super-twisting algorithm (STA) was combined with a non-linear feedback linearisation controller for the inner control loop construction. This strategy can boost the control system’s stability and robustness against external disturbances and modelling uncertainty. The performance analysis of the suggested methods has been carried out via simulation and experimental validation utilizing MATLAB/Simulink with the dSpace 1104 real-time interface.</p>
</abstract>

This research paper proposes a novel design of an efficient combined sliding mode observer (SMO) for induction motor flux and speed estimation. The suggested sensorless technique employs the sliding mode’s second-order approach using a model reference adaptive system (MRAS). The second-order super-twisting control method is free-chattering, which lowers the chattering effect while preserving the same good features as the first-order sliding mode control (SMC). In addition, the conjunction with the MRAS as a separated speed estimator can raise the accuracy and make the observer immune to speed fluctuations, particularly for low-speed applications. Furthermore, in order to achieve effective decoupled flux–torque control, the super-twisting algorithm (STA) was combined with a non-linear feedback linearisation controller for the inner control loop construction. This strategy can boost the control system’s stability and robustness against external disturbances and modelling uncertainty. The performance analysis of the suggested methods has been carried out via simulation and experimental validation utilizing MATLAB/Simulink with the dSpace 1104 real-time interface.

Super-Twisting MRAS Observer-Based Non-linear Direct Flux and Torque Control for Induction Motor Drives

University of M’hamed BOUGARA of Boumerdes

LGEB Laboratory, Electrical Engineering Department

Power Electronics and Drives

This work is licensed under the Creative Commons Attribution 4.0 International License.

This research paper proposes a novel design of an efficient combined sliding mode observer (SMO) for induction motor flux and speed estimation. The suggested...

Super-Twisting MRAS Observer-Based Non-linear Direct Flux and Torque Control for Induction Motor Drives

Publié en ligne: 17 juil. 2024

Pages: 374 - 396

Reçu: 08 avr. 2024

Accepté: 31 mai 2024

DOI: https://doi.org/10.2478/pead-2024-0024

Mots clés
induction motor, sliding mode observer, super-twisting algorithm, model reference adaptive system, feedback linearisation, dSpace 1104

© 2024 Abdelkarim Ammar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Super-Twisting MRAS Observer-Based Non-linear Direct Flux and Torque Control for Induction Motor Drives

Publié en ligne: 17 juil. 2024

Pages: 374 - 396

Reçu: 08 avr. 2024

Accepté: 31 mai 2024

DOI: https://doi.org/10.2478/pead-2024-0024

Mots clésinduction motor, sliding mode observer, super-twisting algorithm, model reference adaptive system, feedback linearisation, dSpace 1104

© 2024 Abdelkarim Ammar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
induction motor, sliding mode observer, super-twisting algorithm, model reference adaptive system, feedback linearisation, dSpace 1104