IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i9p1695-d228370.html
   My bibliography  Save this article

Sensors Fault Diagnosis and Active Fault-Tolerant Control for PMSM Drive Systems Based on a Composite Sliding Mode Observer

Author

Listed:
  • Qinyue Zhu

    (Department of Electrical Engineering, Tongji University, Shanghai 201804, China)

  • Zhaoyang Li

    (Department of Electrical Engineering, Tongji University, Shanghai 201804, China)

  • Xitang Tan

    (Department of Electrical Engineering, Tongji University, Shanghai 201804, China)

  • Dabo Xie

    (Department of Electrical Engineering, Tongji University, Shanghai 201804, China)

  • Wei Dai

    (Department of Electrical Engineering, Tongji University, Shanghai 201804, China)

Abstract

Due to the use of multiple observers and controllers in multi-sensor fault-tolerant control of PMSM drive systems, the algorithm is complex and the system control performance is affected. In view of this, the paper studies multi-sensor fault diagnosis and active fault-tolerant control strategies based on a composite sliding mode observer. With the mathematical model of PMSM built, a design method of the composite sliding mode observer is proposed. A single observer is used to observe and estimate various state variables in the system in real time, which simplifies the implementation of observer-related algorithms. In order to improve the diagnostic accuracy of different types of sensors under different faults, a method for determining fault thresholds is proposed through global search for the maximum residual value. Based on this, a fault diagnosis and active fault-tolerant control strategy is proposed to realize fast switching and reconstruction of feedback signals of closed-loop control systems under different faults of multiple sensors, thus restoring the system performance. Finally, the effectiveness of the proposed algorithm and control strategy is verified by simulation experiments

Suggested Citation

  • Qinyue Zhu & Zhaoyang Li & Xitang Tan & Dabo Xie & Wei Dai, 2019. "Sensors Fault Diagnosis and Active Fault-Tolerant Control for PMSM Drive Systems Based on a Composite Sliding Mode Observer," Energies, MDPI, vol. 12(9), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1695-:d:228370
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/9/1695/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/9/1695/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hao Yan & Yongxiang Xu & Jibin Zou, 2016. "A Phase Current Reconstruction Approach for Three-Phase Permanent-Magnet Synchronous Motor Drive," Energies, MDPI, vol. 9(10), pages 1-16, October.
    2. Takwa Sellami & Hanen Berriri & Sana Jelassi & A Moumen Darcherif & M Faouzi Mimouni, 2017. "Short-Circuit Fault Tolerant Control of a Wind Turbine Driven Induction Generator Based on Sliding Mode Observers," Energies, MDPI, vol. 10(10), pages 1-21, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Masoud Ahmadipour & Hashim Hizam & Mohammad Lutfi Othman & Mohd Amran Mohd Radzi & Nikta Chireh, 2019. "A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine," Energies, MDPI, vol. 12(13), pages 1-18, June.
    2. Ashkan Taherkhani & Farhad Bayat & Kaveh Hooshmandi & Andrzej Bartoszewicz, 2022. "Generalized Sliding Mode Observers for Simultaneous Fault Reconstruction in the Presence of Uncertainty and Disturbance," Energies, MDPI, vol. 15(4), pages 1-20, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wojciech Pietrowski & Konrad Górny, 2020. "Analysis of Torque Ripples of an Induction Motor Taking into Account a Inter-Turn Short-Circuit in a Stator Winding," Energies, MDPI, vol. 13(14), pages 1-19, July.
    2. Zhen Tian & Chengning Zhang & Shuo Zhang, 2017. "Analytical Calculation of Magnetic Field Distribution and Stator Iron Losses for Surface-Mounted Permanent Magnet Synchronous Machines," Energies, MDPI, vol. 10(3), pages 1-12, March.
    3. Fulai Guo & Chengning Zhang, 2019. "Oil-Cooling Method of the Permanent Magnet Synchronous Motor for Electric Vehicle," Energies, MDPI, vol. 12(15), pages 1-11, August.
    4. Mateusz Dybkowski & Szymon Antoni Bednarz, 2019. "Modified Rotor Flux Estimators for Stator-Fault-Tolerant Vector Controlled Induction Motor Drives," Energies, MDPI, vol. 12(17), pages 1-21, August.
    5. Seok-Kyoon Kim, 2017. "Proportional-Type Performance Recovery DC-Link Voltage Tracking Algorithm for Permanent Magnet Synchronous Generators," Energies, MDPI, vol. 10(9), pages 1-17, September.
    6. Koldo Redondo & José Julio Gutiérrez & Izaskun Azcarate & Purificación Saiz & Luis Alberto Leturiondo & Sofía Ruiz de Gauna, 2019. "Experimental Study of the Summation of Flicker Caused by Wind Turbines," Energies, MDPI, vol. 12(12), pages 1-13, June.
    7. Grzegorz Tarchała & Marcin Wolkiewicz, 2019. "Performance of the Stator Winding Fault Diagnosis in Sensorless Induction Motor Drive," Energies, MDPI, vol. 12(8), pages 1-20, April.
    8. Chang-Hwan Park & Dong-Youn Kim & Han-Beom Yeom & Yung-Deug Son & Jang-Mok Kim, 2019. "A Current Reconstruction Strategy Following the Operation Area in a 1-Shunt Inverter System," Energies, MDPI, vol. 12(8), pages 1-16, April.
    9. Nikola Lopac & Neven Bulic & Niksa Vrkic, 2019. "Sliding Mode Observer-Based Load Angle Estimation for Salient-Pole Wound Rotor Synchronous Generators," Energies, MDPI, vol. 12(9), pages 1-22, April.
    10. Guan-Ren Chen & Shih-Chin Yang & Yu-Liang Hsu & Kang Li, 2017. "Position and Speed Estimation of Permanent Magnet Machine Sensorless Drive at High Speed Using an Improved Phase-Locked Loop," Energies, MDPI, vol. 10(10), pages 1-17, October.
    11. Yiguang Chen & Bo Zhang, 2017. "Minimization of the Electromagnetic Torque Ripple Caused by the Coils Inter-Turn Short Circuit Fault in Dual-Redundancy Permanent Magnet Synchronous Motors," Energies, MDPI, vol. 10(11), pages 1-23, November.
    12. Yun-Tao Shi & Xiang Xiang & Li Wang & Yuan Zhang & De-Hui Sun, 2018. "Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System," Energies, MDPI, vol. 11(1), pages 1-20, January.
    13. Yiguang Chen & Xuemin Chen & Yonghuan Shen, 2018. "On-Line Detection of Coil Inter-Turn Short Circuit Faults in Dual-Redundancy Permanent Magnet Synchronous Motors," Energies, MDPI, vol. 11(3), pages 1-31, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1695-:d:228370. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.