IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i24p4656-d997769.html
   My bibliography  Save this article

Adaptive Fuzzy Command Filtered Finite-Time Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Unknown Input Saturation and Unknown Control Directions

Author

Listed:
  • Xiongfeng Deng

    (Key Laboratory of Electric Drive and Control of Anhui Higher Education Institutes, Anhui Polytechnic University, Wuhu 241000, China)

  • Yiqing Huang

    (Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment, Ministry of Education, Anhui Polytechnic University, Wuhu 241000, China)

  • Lisheng Wei

    (Key Laboratory of Electric Drive and Control of Anhui Higher Education Institutes, Anhui Polytechnic University, Wuhu 241000, China)

Abstract

This paper investigates the finite-time consensus tracking control problem of uncertain nonlinear multi-agent systems with unknown input saturation and unknown control directions. An adaptive fuzzy finite-time consensus control law is proposed by combining the fuzzy logic system, command filter, and finite-time control theory. Using the fuzzy logic systems, the uncertain nonlinear dynamics are approximated. Considering the command filter and backstepping control technique, the problem of the so-called “explosion of complexity” in the design of virtual control laws and adaptive updating laws is avoided. Meanwhile, the Nussbaum gain function method is applied to handle the unknown control directions and unknown input saturation problems. Based on the finite-time control theory and Lyapunov stability theory, it was found that all signals in the closed-loop system remained semi-global practical finite-time stable, and the tracking error could converge to a sufficiently small neighborhood of the origin in the finite time. In the end, simulation results were provided to verify the validity of the designed control law.

Suggested Citation

  • Xiongfeng Deng & Yiqing Huang & Lisheng Wei, 2022. "Adaptive Fuzzy Command Filtered Finite-Time Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Unknown Input Saturation and Unknown Control Directions," Mathematics, MDPI, vol. 10(24), pages 1-22, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4656-:d:997769
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/24/4656/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/24/4656/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Wang, Fang & Gao, Yali & Zhou, Chao & Zong, Qun, 2022. "Disturbance observer-based backstepping formation control of multiple quadrotors with asymmetric output error constraints," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    3. Xiongfeng Deng & Xiyu Zhang, 2022. "Adaptive Fuzzy Tracking Control of Uncertain Nonlinear Multi-Agent Systems with Unknown Control Directions and a Dead-Zone Fault," Mathematics, MDPI, vol. 10(15), pages 1-19, July.
    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. Daniel Doz & Darjo Felda & Mara Cotič, 2023. "Demographic Factors Affecting Fuzzy Grading: A Hierarchical Linear Regression Analysis," Mathematics, MDPI, vol. 11(6), pages 1-19, March.

    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. Cui, Guozeng & Xu, Hui & Yu, Jinpeng & Ma, Jiali & Li, Ze, 2023. "Fixed-time distributed adaptive attitude control for multiple QUAVs with quantized input," Applied Mathematics and Computation, Elsevier, vol. 449(C).
    2. 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).
    3. Xu, Lin-Xing & Wang, Yu-Long & Wang, Fei & Long, Yue, 2023. "Event-triggered active disturbance rejection trajectory tracking control for a quadrotor unmanned aerial vehicle," Applied Mathematics and Computation, Elsevier, vol. 449(C).
    4. Xiongfeng Deng & Yiming Yuan & Lisheng Wei & Binzi Xu & Liang Tao, 2022. "Adaptive Neural Tracking Control for Nonstrict-Feedback Nonlinear Systems with Unknown Control Gains via Dynamic Surface Control Method," Mathematics, MDPI, vol. 10(14), pages 1-13, July.

    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:24:p:4656-:d:997769. 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.