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Velocity Sensor Fault-Tolerant Controller for Induction Machine Using Intelligent Voting Algorithm

Author

Listed:
  • Fadi Alyoussef

    (Electrical and Electronics Engineering Department, Institute of Natural and Applied Sciences, Dicle University, Diyarbakır 21280, Turkey)

  • Ahmad Akrad

    (ESTACA’Lab, Ecole Supérieure des Techniques Aéronautiques et de Construction Automobile, 53000 Laval, France)

  • Rabia Sehab

    (ESTACA’Lab, Ecole Supérieure des Techniques Aéronautiques et de Construction Automobile, 53000 Laval, France)

  • Cristina Morel

    (ESTACA’Lab, Ecole Supérieure des Techniques Aéronautiques et de Construction Automobile, 53000 Laval, France)

  • Ibrahim Kaya

    (Electrical and Electronics Engineering Department, Faculty of Engineering, Dicle University, Diyarbakır 21280, Turkey)

Abstract

Nowadays, induction machines (IMs) are widely used in industrial and transportation applications (electric or hybrid ground vehicle or aerospace actuators) thanks to their significant advantages in comparison to other technologies. Indeed, there is a large demand for IMs because of their reliability, robustness, and cost-effectiveness. The objective of this paper is to improve the reliability and performance of the three-phase induction machine in case of mechanical sensor failure. Moreover, this paper will discuss the development and proposal of a fault-tolerant controller (FTC), based on the combination of a vector controller, two virtual sensors (an extended Kalman filter, or EKF, and a sliding mode observer, or SMO) and a neural voting algorithm. In this approach, the vector controller is based on a new structure of a back-stepping sliding mode controller, which incorporates a double integral sliding surface to improve the performance of the induction machine in faulty operation mode. More specifically, this controller improves the machine performance in terms of having a fast response, fewer steady-state errors, and a robust performance in the existence of uncertainty. In addition, two voting algorithms are suggested in this approach. The first is based on neural networks, which are insensitive to parameter variations and do not need to set a threshold. The second one is based on fuzzy logic. Finally, validation is carried out by simulations in healthy and faulty operation modes to prove the feasibility of the proposed FTC.

Suggested Citation

  • Fadi Alyoussef & Ahmad Akrad & Rabia Sehab & Cristina Morel & Ibrahim Kaya, 2022. "Velocity Sensor Fault-Tolerant Controller for Induction Machine Using Intelligent Voting Algorithm," Energies, MDPI, vol. 15(9), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3084-:d:800197
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    References listed on IDEAS

    as
    1. Cristina Morel & Ahmad Akrad & Rabia Sehab & Toufik Azib & Cherif Larouci, 2022. "Open-Circuit Fault-Tolerant Strategy for Interleaved Boost Converters via Filippov Method," Energies, MDPI, vol. 15(1), pages 1-23, January.
    2. Afef Fekih & Saleh Mobayen & Chih-Chiang Chen, 2021. "Adaptive Robust Fault-Tolerant Control Design for Wind Turbines Subject to Pitch Actuator Faults," Energies, MDPI, vol. 14(6), pages 1-13, March.
    Full references (including those not matched with items on IDEAS)

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