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New Sensorless Speed Control of a Hybrid Stepper Motor Based on Fuzzy Sliding Mode Observer

Author

Listed:
  • Chunlei Wang

    (School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
    Tianjin Railway Technical and Vocational College, Tianjin 300240, China)

  • Dongxing Cao

    (School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China)

Abstract

Stepper motors are widely used in industrial and consumer applications due to low-cost, high reliability, and open-loop control capability. Though open-loop features a simple structure, it bears low step resolution, high torque ripple, and low energy efficiency. To improve the performance without increasing hardware cost, a fuzzy sliding mode observer (SMO)-based new sensorless speed control structure is proposed. Unlike the conventional sensorless speed control, it does not use Park and inverse Park transformations to transform currents between a-b and d-q coordinates. Instead, it uses a new current transformation method to generate reference currents of stator windings, which not only reduces the calculation burden of the controller, but also improves the stability of the system. To reduce the chattering, a fuzzy logic controller (FLC) embedded into the SMO is designed to adjust the observer gain adaptively, without using the conventional method that replaces the discontinuous sign function with the continuous, such as sigmoid or saturation function. The effectiveness of the proposed controller is verified using MATLAB/Simulink simulation (R2018b, MathWorks, Natick, MA, USA) and experiment by assessing the speed and position tracking abilities.

Suggested Citation

  • Chunlei Wang & Dongxing Cao, 2020. "New Sensorless Speed Control of a Hybrid Stepper Motor Based on Fuzzy Sliding Mode Observer," Energies, MDPI, vol. 13(18), pages 1-19, September.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4939-:d:416533
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    References listed on IDEAS

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    1. Ming-Shyan Wang & Tse-Ming Tsai, 2017. "Sliding Mode and Neural Network Control of Sensorless PMSM Controlled System for Power Consumption and Performance Improvement," Energies, MDPI, vol. 10(11), pages 1-15, November.
    2. Tomasz Rudnicki, 2020. "Measurement of the PMSM Current with a Current Transducer with DSP and FPGA," Energies, MDPI, vol. 13(1), pages 1-16, January.
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    Cited by:

    1. Chunlei Wang & Dongxing Cao & Xiangxu Qu & Chen Fan, 2022. "An Improved Finite Control Set Model Predictive Current Control for a Two-Phase Hybrid Stepper Motor Fed by a Three-Phase VSI," Energies, MDPI, vol. 15(3), pages 1-17, February.
    2. Yang Liu & Jin Zhao & Quan Yin, 2021. "Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives," Energies, MDPI, vol. 14(8), pages 1-13, April.
    3. Bogdan Bednarski & Krzysztof Jackiewicz & Andrzej Gałecki, 2021. "Influence of Microstepping Signal Shape on Shaft Movement Precision and Torque Variation of the Stepper Motor," Energies, MDPI, vol. 14(19), pages 1-21, September.

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