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Enhancement of Induction Motor Dynamics Using a Novel Sensorless Predictive Control Algorithm

Author

Listed:
  • Hamdi Echeikh

    (Department of Electrical Engineering, National Engineering School of Monastir, Monastir 5035, Tunisia)

  • Mahmoud A. Mossa

    (Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61111, Egypt)

  • Nguyen Vu Quynh

    (Electrical and Electronics Department, Lac Hong University, Dong Nai 810000, Vietnam)

  • Abdelsalam A. Ahmed

    (Electrical Power and Machines Engineering Department, Faculty of Engineering, Tanta University, Tanta 31511, Egypt)

  • Hassan Haes Alhelou

    (Department of Electrical Power Engineering, Faculty of Mechanical and Electrical Engineering, Tishreen University, Lattakia 2230, Syria)

Abstract

The paper introduces a novel predictive voltage control (PVC) procedure for a sensorless induction motor (IM) drive. In the constructed PVC scheme, the direct and quadrature ( d - q ) components of applied voltages are primarily managed instead of controlling the torque and flux as in the classic predictive torque control (PTC) technique. The theoretical basis of the designed PVC is presented and explained in detail, starting from the used cost-function with its relevant components. A comprehensive performance comparison is established between the two controllers, from which the superiorities of the designed PVC over the PTC approach can be easily investigated through the reduced ripples, reduced computation time, and faster dynamics. To sustain the system’s reliability, a combined Luenberger–sliding mode observer (L-SMO) is designed and verified for different operating speeds for the two controllers. The Luenberger component is concerned with estimating the stator current, rotor flux, and rotor speed. Meanwhile, the sliding mode term is used to ensure the system’s robustness against any disturbance. The verification of PVC’s validity is outlined through performing a performance analysis using the Matlab/Simulink software. The results illustrate that the IM dynamic is significantly improved when considering the constructed PVC compared with the IM dynamics under the PTC. In addition, the designed L-SMO observer has effectively proved its ability to achieve definite parameters and variable estimation.

Suggested Citation

  • Hamdi Echeikh & Mahmoud A. Mossa & Nguyen Vu Quynh & Abdelsalam A. Ahmed & Hassan Haes Alhelou, 2021. "Enhancement of Induction Motor Dynamics Using a Novel Sensorless Predictive Control Algorithm," Energies, MDPI, vol. 14(14), pages 1-28, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4377-:d:597946
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    References listed on IDEAS

    as
    1. Mahmoud A. Mossa & Nguyen Vu Quynh & Hamdi Echeikh & Ton Duc Do, 2020. "Deadbeat-Based Model Predictive Voltage Control for a Sensorless Five-Phase Induction Motor Drive," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-30, July.
    2. Haixia Li & Jican Lin & Ziguang Lu, 2019. "Three Vectors Model Predictive Torque Control Without Weighting Factor Based on Electromagnetic Torque Feedback Compensation," Energies, MDPI, vol. 12(7), pages 1-19, April.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Abderrahman El Idrissi & Aziz Derouich & Said Mahfoud & Najib El Ouanjli & Ahmed Chantoufi & Ameena Saad Al-Sumaiti & Mahmoud A. Mossa, 2022. "Bearing Fault Diagnosis for an Induction Motor Controlled by an Artificial Neural Network—Direct Torque Control Using the Hilbert Transform," Mathematics, MDPI, vol. 10(22), pages 1-32, November.

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