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Communication Dans Un Congrès Année : 2021

A New Approach for Online Stator Fault Diagnosis in PMSM Based on Robust Gain Scheduled H∞ LPV Current Observer

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D. Khamari
  • Fonction : Auteur
C. Bouchareb
  • Fonction : Auteur
I. Benlaloui
  • Fonction : Auteur
F. Benmessaoud
  • Fonction : Auteur
T. Boutabba
  • Fonction : Auteur

Résumé

A new online Stator winding faults detection in PMSM based on robust gain scheduled H∞ LPV current observer is proposed in this paper. The stator resistance was taking as varying parameters to improve the robustness of current observer. Therefore, the original synthesis is based on LPV systems theory. The question of stability is addressed in the terms of Lyapunov quadratic stability by using an LMI convex optimization. The robust residual generation can be formulated as an optimization problem. On the one hand, this formulation reduces residual sensitivity compared to varying parameters. On the other hand, it works to maximize this sensitivity compared to faults. The effectiveness of the proposed approach can be demonstrated through simulation results. \textcopyright 2021 IEEE.
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Dates et versions

hal-03681740 , version 1 (30-05-2022)

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Citer

D. Khamari, C. Bouchareb, I. Benlaloui, F. Benmessaoud, T. Boutabba, et al.. A New Approach for Online Stator Fault Diagnosis in PMSM Based on Robust Gain Scheduled H∞ LPV Current Observer. International Conference on Control, Automation and Diagnosis (ICCAD’21), Nov 2021, Grenoble, France. ⟨10.1109/ICCAD52417.2021.9638764⟩. ⟨hal-03681740⟩

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