IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i7p1182-d787043.html
   My bibliography  Save this article

Adaptive Neural Network Sliding Mode Control for a Class of SISO Nonlinear Systems

Author

Listed:
  • Bin Li

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China)

  • Jiahao Zhu

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China)

  • Ranran Zhou

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China)

  • Guoxing Wen

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China
    College of Science, Binzhou University, Binzhou 256600, China)

Abstract

In this article, a sliding mode control (SMC) is proposed on the basis of an adaptive neural network (NN) for a class of Single-Input–Single-Output (SISO) nonlinear systems containing unknown dynamic functions. Since the control objective is to steer the system states to track the given reference signals, the SMC method is considered by employing the adaptive neural network (NN) strategy for dealing with the unknown dynamic problem. In order to compress the impaction coming from chattering phenomenon (which inherently exists in most SMC methods because of the discontinuous switching term), the boundary layer technique is considered. The basic design idea is to introduce a continuous proportional function to replace the discontinuous switching control term inside the boundary layer so that the chattering can be effectively alleviated. Finally, both Lyapunov theoretical analysis and computer numerical simulation are used to verify the effectiveness of the proposed SMC method.

Suggested Citation

  • Bin Li & Jiahao Zhu & Ranran Zhou & Guoxing Wen, 2022. "Adaptive Neural Network Sliding Mode Control for a Class of SISO Nonlinear Systems," Mathematics, MDPI, vol. 10(7), pages 1-12, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1182-:d:787043
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/7/1182/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/7/1182/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Issaraporn Khonchaiyaphum & Nayika Samorn & Thongchai Botmart & Kanit Mukdasai, 2021. "Finite-Time Passivity Analysis of Neutral-Type Neural Networks with Mixed Time-Varying Delays," Mathematics, MDPI, vol. 9(24), pages 1-26, December.
    2. Kening Li & Jianyong Cao & Fan Yu, 2013. "Study on the Nonsingular Problem of Fractional-Order Terminal Sliding Mode Control," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, August.
    3. Igor Boiko, 2013. "Chattering in sliding mode control systems with boundary layer approximation of discontinuous control," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(6), pages 1126-1133.
    4. Soares, Orlando & Gonçalves, Henrique & Martins, António & Carvalho, Adriano, 2010. "Nonlinear control of the doubly-fed induction generator in wind power systems," Renewable Energy, Elsevier, vol. 35(8), pages 1662-1670.
    5. Li, Zheng & Wang, Fang & Zhu, Ruitai, 2021. "Finite-time adaptive neural control of nonlinear systems with unknown output hysteresis," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    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. Justo, Jackson John & Mwasilu, Francis & Jung, Jin-Woo, 2015. "Doubly-fed induction generator based wind turbines: A comprehensive review of fault ride-through strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 447-467.
    2. Baoyu Huo & Mingjun Du & Zhiguo Yan, 2023. "Adaptive Sliding Mode Attitude Tracking Control for Rigid Spacecraft Considering the Unwinding Problem," Mathematics, MDPI, vol. 11(20), pages 1-16, October.
    3. M. Abdelbasset Mahboub & Said Drid & M. A. Sid & Ridha Cheikh, 2017. "Sliding mode control of grid connected brushless doubly fed induction generator driven by wind turbine in variable speed," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 788-798, November.
    4. Wu, Ziwen & Zhang, Tianping & Xia, Xiaonan & Hua, Yu, 2022. "Finite-time adaptive neural command filtered control for non-strict feedback uncertain multi-agent systems including prescribed performance and input nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    5. Liu, Shanlin & Niu, Ben & Zong, Guangdeng & Zhao, Xudong & Xu, Ning, 2022. "Adaptive fixed-time hierarchical sliding mode control for switched under-actuated systems with dead-zone constraints via event-triggered strategy," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    6. Yuxuan Liu, 2024. "Command-Filtered Nussbaum Design for Nonlinear Systems with Unknown Control Direction and Input Constraints," Mathematics, MDPI, vol. 12(14), pages 1-17, July.
    7. Habib Benbouhenni & Nicu Bizon, 2021. "Third-Order Sliding Mode Applied to the Direct Field-Oriented Control of the Asynchronous Generator for Variable-Speed Contra-Rotating Wind Turbine Generation Systems," Energies, MDPI, vol. 14(18), pages 1-20, September.
    8. Zhang, Guodong & Cao, Jinde, 2023. "New results on fixed/predefined-time synchronization of delayed fuzzy inertial discontinuous neural networks: Non-reduced order approach," Applied Mathematics and Computation, Elsevier, vol. 440(C).
    9. Quanxin Zhu, 2022. "Nonlinear Systems: Dynamics, Control, Optimization and Applications to the Science and Engineering," Mathematics, MDPI, vol. 10(24), pages 1-2, December.
    10. El-Kharashi, Eyhab & Farid, Azmy Wadie, 2015. "Accurate assessment of the output energy from the doubly fed induction generators," Energy, Elsevier, vol. 93(P1), pages 406-415.
    11. Hassen Moussa & Saber Krim & Hichem Kesraoui & Majdi Mansouri & Mohamed Faouzi Mimouni, 2024. "Loss Model Control for Efficiency Optimization and Advanced Sliding Mode Controllers with Chattering Attenuation for Five-Phase Induction Motor Drive," Energies, MDPI, vol. 17(16), pages 1-37, August.
    12. Boutoubat, M. & Mokrani, L. & Machmoum, M., 2013. "Control of a wind energy conversion system equipped by a DFIG for active power generation and power quality improvement," Renewable Energy, Elsevier, vol. 50(C), pages 378-386.
    13. Wang, Kun-Peng & Ding, Dong & Tang, Ze & Feng, Jianwen, 2022. "Leader-Following consensus of nonlinear multi-agent systems with hybrid delays: Distributed impulsive pinning strategy," Applied Mathematics and Computation, Elsevier, vol. 424(C).
    14. Aslmostafa, Ehsan & Mirzaei, Mohammad Javad & Asadollahi, Mostafa & Badamchizadeh, Mohammad Ali, 2021. "Synchronization problem for a class of multi-input multi-output systems with terminal sliding mode control based on finite-time disturbance observer: Application to Chameleon chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    15. Jabbari Asl, Hamed & Yoon, Jungwon, 2016. "Power capture optimization of variable-speed wind turbines using an output feedback controller," Renewable Energy, Elsevier, vol. 86(C), pages 517-525.
    16. Cui, Di & Zou, Wencheng & Guo, Jian & Xiang, Zhengrong, 2022. "Neural network-based adaptive finite-time tracking control of switched nonlinear systems with time-varying delay," Applied Mathematics and Computation, Elsevier, vol. 428(C).
    17. Kusiak, Andrew & Zhang, Zijun & Verma, Anoop, 2013. "Prediction, operations, and condition monitoring in wind energy," Energy, Elsevier, vol. 60(C), pages 1-12.

    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:10:y:2022:i:7:p:1182-:d:787043. 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.