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Robust speed regulation of indirect vector control induction motor using fuzzy logic controllers based on optimization algorithms

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Abstract

Currently, in high-performance applications, the vector control (VC) scheme of induction motor (IM) is widely employed in industry. The VC scheme has significant features of decoupling torque and flux; also, its hardware implementation is easier. Conventionally, PID control schemes are frequently used for variable speed operation. However, the performance of the VC scheme is limited over a wide range of speed operation because of de-tuning caused by parameter uncertainties. To address the aforementioned challenging problem, adaptive and robust control strategies are mostly implemented. This paper presents various novel, adaptive, and robust control strategies, namely (a) fuzzy logic controller (FLC) based on Levenberg–Marquardt algorithm (LMA), (b) FLC based on steepest descent algorithm (SDA), (c) FLC based on Newton algorithm (NA), and (d) FLC based on Gauss–Newton algorithm (GNA) for the indirect vector control (IVC) three-phase IM. The focal motive is to accomplish fast dynamic response with fault-tolerant capability, load disturbance rejection qualities, insensitivity to the parameter uncertainties, robustness to speed variation, and to acquire maximum efficiency as well as torque. The \(d-q\) modeling of the IVC IM in the synchronous reference frame and space vector pulse width modulation (SVPWM) employed in inverter are designed in MATLAB/Simulink. Our work also presents critical, analytical, and comparative assessment of the proposed controllers with traditional tuned PI control strategy for the electrical faults perturbation, load disturbances, speed variations, and parameter uncertainties. Furthermore, the simulation results of the above-mentioned designed control strategies validated robust, smooth, and faster response with permissible overshoot, undershoot, settling time, and rise time for the IVC IM drive system, compared to prior works.

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Abbreviations

\(v_{sd},v_{sq}\) :

Synchronous frame (dq-axis) stator voltages.

\(i_{sd},i_{sq}\) :

Synchronous frame (dq-axis) stator currents.

\(\lambda _{sd},\lambda _{sq}\) :

Synchronous frame (dq-axis) stator fluxes.

\(v_{rd},v_{rq}\) :

Synchronous frame (dq-axis) rotor voltages.

\(i_{rd},i_{rq}\) :

Synchronous frame (dq-axis) rotor currents.

\(\lambda _{rd},\lambda _{rq}\) :

Synchronous frame (dq-axis) rotor fluxes.

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

Stator and rotor inductances, respectively.

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

Stator and rotor resistances, respectively.

\(L_{m}\) :

Mutual inductance.

\(\omega _{m}\) :

Mechanical rotor speed.

\(\omega _{e}\) :

Electrical synchronous speed.

\(\omega _{sl}\) :

Angular slip speed.

\(\omega _{d}\) :

Electrical synchronous speed.

\(\omega _{dA}\) :

Angular slip speed.

\(\theta _{r}\) :

Rotor angle.

\(\theta _{f}\) :

Field angle.

\(T_{L}\) :

Load torque.

\(T_{em}\) :

Electromagnetic torque.

\(J_{eq}\) :

Moment of inertia.

\(T_{r}\) :

Rotor time’s constant.

d(t):

Uncertainties.

\(\mu \) :

Combination coefficient.

\(\lambda \) :

Regularization constant.

\(\mu _{i}\) :

Membership function.

\(c_{i}(k)\) :

Center of membership function.

\(\sigma _{i}(k)\) :

Variance of membership function.

\(b_{i}(k)\) :

Output membership function.

\(J_{k}\) :

Jacobian matrix.

H :

Hessian matrix.

\(f_{m}\) :

Controller output

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, University of Management and Technology, Sialkot Campus, Sialkot, Pakistan

    Kamran Zeb, Waqar Uddin, Aun Haider & S. Belal

  2. Department of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad, Pakistan

    C. A. Mehmood

  3. School of Electrical Engineering, Pusan National University, San 30, ChangJeon 2 Dong, KeumJeong-gu, Pusan, South Korea

    Kamran Zeb, M. A. Khan & H. J. Kim

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  1. Kamran Zeb
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  2. Waqar Uddin
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  3. Aun Haider
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  4. S. Belal
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Correspondence to Kamran Zeb.

Appendices

Appendix

Machine nominal parameters

Rated power 3 HP/2.4 KW, line voltage 460 V (L-L, rms), phases 3, number of poles 4, system frequency 60 Hz, full-load slip 1.72%, stator resistance \(1.77 \,\Omega \), rotor resistance \(1.34\,\Omega \), stator leakage resistance \(5.25\,\Omega \), rotor leakage resistance \(4.57\,\Omega \), mutual inductance \(139\,\Omega \), moment of inertia \(70\, \mathrm{kg\,m^{2}}\), rated torque 12.6444, full-load current 4 A, full-load efficiency 88.5%, power factor 80%, full-load speed 1750 rpm, iron losses 78 W, and mechanical (friction\(+\)windage) losses 24 W (Table 4).

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Zeb, K., Uddin, W., Haider, A. et al. Robust speed regulation of indirect vector control induction motor using fuzzy logic controllers based on optimization algorithms. Electr Eng 100, 787–802 (2018). https://doi.org/10.1007/s00202-017-0553-z

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