IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i17p2124-d627338.html
   My bibliography  Save this article

Multiple Loop Fuzzy Neural Network Fractional Order Sliding Mode Control of Micro Gyroscope

Author

Listed:
  • Yunmei Fang

    (College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China)

  • Fang Chen

    (College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China)

  • Juntao Fei

    (College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China
    Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology, Changzhou 213022, China)

Abstract

In this paper, an adaptive double feedback fuzzy neural fractional order sliding control approach is presented to solve the problem that lumped parameter uncertainties cannot be measured and the parameters are unknown in a micro gyroscope system. Firstly, a fractional order sliding surface is designed, and the fractional order terms can provide additional freedom and improve the control accuracy. Then, the upper bound of lumped nonlinearities is estimated online using a double feedback fuzzy neural network. Accordingly, the gain of switching law is replaced by the estimated value. Meanwhile, the parameters of the double feedback fuzzy network, including base widths, centers, output layer weights, inner gains, and outer gains, can be adjusted in real time in order to improve the stability and identification efficiency. Finally, the simulation results display the performance of the proposed approach in terms of convergence speed and track speed.

Suggested Citation

  • Yunmei Fang & Fang Chen & Juntao Fei, 2021. "Multiple Loop Fuzzy Neural Network Fractional Order Sliding Mode Control of Micro Gyroscope," Mathematics, MDPI, vol. 9(17), pages 1-20, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:17:p:2124-:d:627338
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/17/2124/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/17/2124/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Juntao Fei & Xiao Liang, 2018. "Adaptive Backstepping Fuzzy Neural Network Fractional-Order Control of Microgyroscope Using a Nonsingular Terminal Sliding Mode Controller," Complexity, Hindawi, vol. 2018, pages 1-12, September.
    2. Juntao Fei & Zhilin Feng, 2019. "Adaptive Fuzzy Super-Twisting Sliding Mode Control for Microgyroscope," Complexity, Hindawi, vol. 2019, pages 1-13, February.
    Full references (including those not matched with items on IDEAS)

    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. Zhe Wang & Juntao Fei, 2019. "Novel Fuzzy Neural Nonsingular Terminal Sliding Mode Control of MEMS Gyroscope," Complexity, Hindawi, vol. 2019, pages 1-15, December.
    2. Xiao Liang & Juntao Fei, 2019. "Adaptive fractional fuzzy sliding mode control of microgyroscope based on backstepping design," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-21, June.
    3. Hongbin Wang & Bo Su & Yueling Wang & Jing Gao, 2019. "Adaptive Sliding Mode Fixed-Time Tracking Control Based on Fixed-Time Sliding Mode Disturbance Observer with Dead-Zone Input," Complexity, Hindawi, vol. 2019, pages 1-14, August.

    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:jmathe:v:9:y:2021:i:17:p:2124-:d:627338. 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.