IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i4p988-d1069088.html
   My bibliography  Save this article

Prescribed Settling Time Adaptive Neural Network Consensus Control of Multiagent Systems with Unknown Time-Varying Input Dead-Zone

Author

Listed:
  • Wenqiang Wu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Jiarui Liu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Fangyi Li

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
    Key Laboratory for Safety Control of Bridge Engineering, Ministry of Education and Hunan Province, Changsha University of Science and Technology, Changsha 410114, China)

  • Yuanqing Zhang

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Zikai Hu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

Abstract

For a class of multiagent systems with an unknown time-varying input dead-zone, a prescribed settling time adaptive neural network consensus control method is developed. In practical applications, some control signals are difficult to use effectively due to the extensive existence of an input dead-zone. Moreover, the time-varying input gains further seriously degrade the performance of the systems and even cause system instability. In addition, multiagent systems need frequent communication to ensure a system’s consistency. This may lead to communication congestion. To solve this problem, an event-triggered adaptive neural network control method is proposed. Further, combined with the prescribed settling time transform function, the developed consensus method greatly increases the convergence rate. It is demonstrated that all followers of multiagent systems can track the virtual leader within a prescribed time and not exhibit Zeno behavior. Finally, the theoretical analysis and simulation verify the effectiveness of the designed control method.

Suggested Citation

  • Wenqiang Wu & Jiarui Liu & Fangyi Li & Yuanqing Zhang & Zikai Hu, 2023. "Prescribed Settling Time Adaptive Neural Network Consensus Control of Multiagent Systems with Unknown Time-Varying Input Dead-Zone," Mathematics, MDPI, vol. 11(4), pages 1-21, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:4:p:988-:d:1069088
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/4/988/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/4/988/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xu, Jiahong & Wang, Lijie & Liu, Yang & Sun, Jize & Pan, Yingnan, 2022. "Finite-time adaptive optimal consensus control for multi-agent systems subject to time-varying output constraints," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    2. Lili Zhang & Bing Chen & Chong Lin & Yun Shang, 2021. "Fuzzy adaptive finite-time consensus tracking control for nonlinear multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(7), pages 1346-1358, May.
    3. Zhao, Guangtong & Cao, Liang & Li, Xiaomeng & Zhou, Qi, 2022. "Observer-based dynamic event-triggered control for nonstrict-feedback stochastic nonlinear multiagent systems," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    4. Wu, Li-Bing & Park, Ju H. & Xie, Xiang-Peng & Liu, Ya-Juan & Yang, Zhi-Chun, 2020. "Event-triggered adaptive asymptotic tracking control of uncertain nonlinear systems with unknown dead-zone constraints," Applied Mathematics and Computation, Elsevier, vol. 386(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. 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. Zhai, Ganghui & Tian, Engang & Luo, Yuqiang & Liang, Dong, 2024. "Data-driven optimal output regulation for unknown linear discrete-time systems based on parameterization approach," Applied Mathematics and Computation, Elsevier, vol. 461(C).
    3. Yi, Jiale, 2023. "Adaptive fuzzy connectivity-preserving consensus protocols for stochastic strict-feedback nonlinear MASs subject to unmeasured periodic disturbances," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    4. Vijayakumar, M. & Sakthivel, R. & Mohammadzadeh, Ardashir & Karthick, S.A. & Marshal Anthoni, S., 2021. "Proportional integral observer based tracking control design for Markov jump systems," Applied Mathematics and Computation, Elsevier, vol. 410(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. Hu, Yifan & Liu, Wenhui & Liu, Guobao, 2022. "Adaptive finite‐time event‐triggered control for uncertain nonlinearly parameterized systems with unknown control direction and actuator failures," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    7. 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).
    8. 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).
    9. Ju, Xinxu & Jia, Xianglei & Shi, Xiaocheng & Yu, Shan’en, 2022. "Adaptive output feedback event-triggered tracking control for nonlinear systems with unknown control coefficient," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    10. Yuan, Manman & Zhai, Junyong & Ye, Hui, 2022. "Adaptive output feedback control for a class of switched stochastic nonlinear systems via an event-triggered strategy," Applied Mathematics and Computation, Elsevier, vol. 422(C).
    11. Jiang Wu & Yujie Xu & Hao Xie & Yao Zou, 2023. "Finite-Time Bounded Tracking Control for a Class of Neutral Systems," Mathematics, MDPI, vol. 11(5), pages 1-16, February.
    12. Tang, Tianfeng & Qin, Gang & Zhang, Bin & Cheng, Jun & Cao, Jinde, 2024. "Event-based asynchronous state estimation for Markov jump memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    13. 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).

    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:11:y:2023:i:4:p:988-:d:1069088. 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.