IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v435y2022ics0096300322005446.html
   My bibliography  Save this article

Improved Adaptive Fuzzy Control for Non-Strict Feedback Nonlinear Systems: a Dynamic Compensation System Approach

Author

Listed:
  • Wu, Dawei
  • Sun, Yonghui
  • Xia, Rongsheng
  • Lu, Shumin

Abstract

This paper investigates the tracking control problem for uncertain nonlinear non-strict feedback systems (NSFSs) in the presence of full-state constraints and unmeasured disturbances. It is of great practical significance to realize the full-state constraint under disturbed conditions. In view of the non-strict feedback problem, a novel design framework of the state feedback control is given based on the newly proposed dynamic compensation system (DCS). Different from the traditional backstepping, the estimated signal based on the adaptive fuzzy system is indirectly introduced into the virtual and actual control laws through the DCS, which has the advantage of avoiding the algebraic-loop problem in NSFSs. Accordingly, the disturbance observer (DO) design method is improved based on this framework. Integrating the DCS into the DO design avoids the coupling problem between the disturbance and the unknown nonlinear function. An improved barrier Lyapunov function (BLF) is designed by introducing the concept of the inducible factor, and full-state constraints can be guaranteed after a transitional period for any initial state. By combining the DCS, the DO and the improved BLF, a novel adaptive fuzzy tracking control law is constructed, and all the signals in the closed-loop system are semiglobally uniformly ultimately bounded. Finally, the theoretical analysis and simulation results show that all states meet the corresponding constraints while meeting the stability.

Suggested Citation

  • Wu, Dawei & Sun, Yonghui & Xia, Rongsheng & Lu, Shumin, 2022. "Improved Adaptive Fuzzy Control for Non-Strict Feedback Nonlinear Systems: a Dynamic Compensation System Approach," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    • Handle: RePEc:eee:apmaco:v:435:y:2022:i:c:s0096300322005446
    DOI: 10.1016/j.amc.2022.127470
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300322005446
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2022.127470?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yongchao Liu & Qidan Zhu, 2022. "Adaptive fuzzy asymptotic control for switched nonlinear systems with state constraints," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(5), pages 922-933, April.
    2. Jin-Zi Yang & Yuan-Xin Li, 2020. "Fuzzy adaptive asymptotic tracking of uncertain nonlinear systems with full states constraints," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(16), pages 3550-3562, December.
    3. Yingxue Hou & Shaocheng Tong & Yongming Li, 2016. "Adaptive fuzzy backstepping control for a class of switched nonlinear systems with actuator faults," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(15), pages 3581-3590, November.
    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. Truong, Hoai Vu Anh & Phan, Van Du & Tran, Duc Thien & Ahn, Kyoung Kwan, 2024. "A novel observer-based neural-network finite-time output control for high-order uncertain nonlinear systems," Applied Mathematics and Computation, Elsevier, vol. 475(C).

    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. Wang, Le & Sun, Wei & Su, Shun-Feng, 2022. "Adaptive asymptotic tracking control for nonlinear systems with state constraints and input saturation," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    2. Wang, Yuanqing & Xu, Ning & Liu, Yajuan & Zhao, Xudong, 2021. "Adaptive fault-tolerant control for switched nonlinear systems based on command filter technique," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    3. Yoo, Sung Jin, 2021. "Decentralized event-triggered adaptive control of a class of uncertain interconnected nonlinear systems using local state feedback corrupted by unknown injection data," Applied Mathematics and Computation, Elsevier, vol. 399(C).
    4. Yan, Yan & Wu, Libing & Yan, Weijun & Hu, Yuhan & Zhao, Nannan & Chen, Ming, 2022. "Finite-time event-triggered fault-tolerant control for a family of pure-feedback systems," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    5. Chuanfeng Li & Hao Wu & Zhile Yang & Yongji Wang & Zeyu Sun, 2017. "A Novel SHLNN Based Robust Control and Tracking Method for Hypersonic Vehicle under Parameter Uncertainty," Complexity, Hindawi, vol. 2017, pages 1-14, October.
    6. Hu, Yifan & Liu, Wenhui, 2023. "Adaptive fuzzy dynamic surface control for nonstrict-feedback nonlinear state constrained systems with input dead-zone via event-triggered sampling," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    7. Xiongfeng Deng & Jiakai Wang, 2022. "Fuzzy-Based Adaptive Dynamic Surface Control for a Type of Uncertain Nonlinear System with Unknown Actuator Faults," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    8. He, Hangfeng & Qi, Wenhai & Kao, Yonggui, 2021. "HMM-based adaptive attack-resilient control for Markov jump system and application to an aircraft model," Applied Mathematics and Computation, Elsevier, vol. 392(C).

    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:eee:apmaco:v:435:y:2022:i:c:s0096300322005446. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.