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Feedback Linearization Based Robust Control for Linear Permanent Magnet Synchronous Motors

Author

Listed:
  • Yung-Te Chen

    (Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taipei 106, Taiwan)

  • Chi-Shan Yu

    (Department of Digital Technology Design, National Taipei University of Education, Taipei 106, Taiwan)

  • Ping-Nan Chen

    (Department of Biomedical Engineering, National Defense Medical Center, Taipei 114, Taiwan)

Abstract

In this study, we designed a feedback linearization control strategy for linear permanent magnet synchronous motors (LPMSMs) as well as a robust control mechanism. First, the highly nonlinear system was transformed into an exact linear system by the feedback linearization technique. Then, we designed a robust controller to mitigate the impact of system parameter disturbances on system performance. This novel robust feedback controller can be applied to electromagnetic force, speed and position control loops in linear motors, correct the errors created by uncertainty factors in the entire system in real time, and set the system’s settling time based on the application environment of the plant. Finally, we performed simulations and experiments using a PC-based motor control system, which demonstrated that the proposed robust feedback controller can achieve good performance in the controlled system with robust anti-disturbance control.

Suggested Citation

  • Yung-Te Chen & Chi-Shan Yu & Ping-Nan Chen, 2020. "Feedback Linearization Based Robust Control for Linear Permanent Magnet Synchronous Motors," Energies, MDPI, vol. 13(20), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5242-:d:425331
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    References listed on IDEAS

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    1. Xiaoqi Song & Dezhi Xu & Weilin Yang & Yan Xia & Bin Jiang, 2018. "Improved Model-Free Adaptive Sliding-Mode-Constrained Control for Linear Induction Motor considering End Effects," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, May.
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    Cited by:

    1. Lu Liu & Yun Zeng, 2023. "Intelligent ISSA-Based Non-Singular Terminal Sliding-Mode Control of DC–DC Boost Converter Feeding a Constant Power Load System," Energies, MDPI, vol. 16(13), pages 1-23, June.
    2. Marcel Nicola & Claudiu-Ionel Nicola, 2022. "Improvement of Linear and Nonlinear Control for PMSM Using Computational Intelligence and Reinforcement Learning," Mathematics, MDPI, vol. 10(24), pages 1-34, December.

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