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Improvement of the induction motor sensorless control based on the type-2 fuzzy logic

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Abstract

This paper presents MRAS speed sensorless control of induction motor using type-2 fuzzy logic controller (T2FLC). These controllers replace the PI ones, in the new MRAS strategy proposed in Benlaloui et al. (IEEE Trans Energy Convers 30(2):588–595, 2015), in order to improve the induction motor performances and robustness at low speed region. Indeed, the choice of these controllers is made because of their adaptation-based schemes which permit to handle nonlinear uncertain systems without the need of precise mathematical model required when using PI controllers. Comparative study had shown a better rejection of disturbance and high insensitivity to stator resistance compared to the PI and the T1FLC controllers. The effectiveness of the proposed speed-based T2FLC estimation method and its good robustness are validated by simulation and by experimental results.

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Abbreviations

MRAS:

Model Reference Adaptive System

T2FLC:

Type-2 Fuzzy Logic Controller

IM:

Induction machines

FOC:

Field-oriented control

PI:

Proportional–integral

IFOC:

Indirect field-oriented control

s, r :

Rotor and stator indices

d, q :

Direct and quadrate indices for orthogonal components

P :

Number of pairs poles

Ω :

Rotor speed (rd/s)

ω r :

Induced rotor current frequency (rd/s)

J in :

Inertia

Γ :

Unknown torque

*:

Symbol indicating the command value

\(\overline{x}^{*}\) :

Complex conjugate

\(R_{{\text{s}}} ,R_{{\text{r}}}\) :

Stator and rotor resistances

\(L_{s} ,L_{r}\) :

Stator and rotor inductances

\(T_{{\text{s}}} ,T_{{\text{r}}}\) :

Stator and rotor time constants (Ts,r = Ls,r/Rs, r)

σ :

Leakage flux total coefficient (σ = 1 − M2/LrLs)

M :

Mutual inductance

ω :

Mechanical rotor frequency (rd/s)

ω s :

Stator current frequency (rd/s)

f :

Coefficient of viscous

Γ e :

Electromagnetic torque

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Author information

Authors and Affiliations

  1. Université 8 mai 1945, Guelma, Algeria

    Idriss Benlaloui

  2. LSPIE Laboratory, Electrical Engineering Department, University of Batna2, Fesdis, Algeria

    Idriss Benlaloui, Abderrahmane Khemis, Dalila Khamari & Said Drid

  3. University of Picardie Jules Verne, LTI (EA, 3899), 13 av F. Mitterrand, 02880, Cuffies, France

    Larbi Chrifi-Alaoui

  4. Laboratory of Engineering Sciences (LSI), University of Sidi Mohamed Benabdellah, Fez, Morocco

    Mohammed Ouriagli

  5. University of Khenchela, EI-Hamma, Algeria

    Abderrahmane Khemis

Authors
  1. Idriss Benlaloui
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  2. Larbi Chrifi-Alaoui
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  3. Mohammed Ouriagli
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  4. Abderrahmane Khemis
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  5. Dalila Khamari
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  6. Said Drid
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Correspondence to Idriss Benlaloui.

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Appendices

Appendix

Machine parameters and rated values

Rr = 5.1498 Ω; Rs = 12.75 Ω; M = 0. 4331 H; Ls = 0. 4991 H; Lr = 0.4331 H; J = 0.0035 kg m2; f = 0.001 Nm s/rd; Pn = 0.9 kW; n = 1400 rpm; p = 2; f = 50 Hz; load torque = 10 Nm.

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Benlaloui, I., Chrifi-Alaoui, L., Ouriagli, M. et al. Improvement of the induction motor sensorless control based on the type-2 fuzzy logic. Electr Eng 103, 1473–1482 (2021). https://doi.org/10.1007/s00202-020-01178-1

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  • DOI: https://doi.org/10.1007/s00202-020-01178-1

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