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Related Experiment Videos

Position tracking control of saturated LSRM.

Drago Dolinar1, Gorazd Stumberger, Miro Milanovic

  • 1Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, Slovenia. dolinar@uni-mb.si

ISA Transactions
|November 13, 2004
PubMed
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This study improves linear synchronous reluctance motor (LSRM) tracking control by incorporating magnetic saturation into the motor model. This enhanced control reduces speed and position errors, especially at low speeds.

Area of Science:

  • Electrical Engineering
  • Control Systems
  • Motor Drives

Background:

  • Linear Synchronous Reluctance Motors (LSRM) are crucial in various industrial applications.
  • Accurate tracking control, especially at low speeds, is a persistent challenge.
  • Magnetic saturation in LSRMs significantly affects motor dynamics and control performance.

Purpose of the Study:

  • To design an advanced tracking control for LSRM drives.
  • To enhance tracking performance, particularly at very low speeds.
  • To investigate the impact of magnetic saturation on control accuracy and motor stiffness.

Main Methods:

  • Development of an extended nonlinear dynamic LSRM model incorporating magnetic saturation.
  • Experimental determination of flux linkages as functions of direct and quadrature axis currents.

Related Experiment Videos

  • Implementation of an input-output linearizing tracking control strategy.

    • Main Results:

    • The proposed control with magnetic saturation demonstrated superior performance compared to models without saturation.
    • Significant reductions in position and speed errors were observed.
    • Improved motor stiffness was achieved, enhancing overall drive stability.

    Conclusions:

    • Including magnetic saturation in the LSRM model is critical for high-performance tracking control.
    • The developed control strategy effectively mitigates errors at low speeds.
    • The enhanced control offers a practical solution for improving LSRM drive precision despite increased computational load.