IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v399y2021ics0096300321000485.html
   My bibliography  Save this article

Topology reconstruction based fault identification for uncertain multi-agent systems with application to multi-axis motion control system

Author

Listed:
  • Zhu, Jun-Wei
  • Zhou, Qiao-Qian
  • Wu, Li-Bing
  • Xu, Jian-Ming
  • Wang, Xin

Abstract

In the industrial multi-agent systems, the effect of the faults occurring on any subsystem may diffuse to the whole system through network topology and cause the control performance degradation. This paper aims to solve the issue of fault identification for uncertain multi-agent systems with sensor faults. Firstly, a randomized cooperative fault detection system composed by a group of decoupled filters is presented, where a joint fault detection performance assessment scheme is designed. On this basis, a novel topology reconstruction-based fault isolation strategy is proposed. Finally, two case studies on the multi-axis motion control system are conducted, and the results illustrate the effectiveness of the proposed framework.

Suggested Citation

  • Zhu, Jun-Wei & Zhou, Qiao-Qian & Wu, Li-Bing & Xu, Jian-Ming & Wang, Xin, 2021. "Topology reconstruction based fault identification for uncertain multi-agent systems with application to multi-axis motion control system," Applied Mathematics and Computation, Elsevier, vol. 399(C).
    • Handle: RePEc:eee:apmaco:v:399:y:2021:i:c:s0096300321000485
    DOI: 10.1016/j.amc.2021.126000
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321000485
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2021.126000?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. Guo, Xiyue & Liang, Hongjing & Pan, Yingnan, 2020. "Observer-Based Adaptive Fuzzy Tracking Control for Stochastic Nonlinear Multi-Agent Systems with Dead-Zone Input," Applied Mathematics and Computation, Elsevier, vol. 379(C).
    2. Li, Tao & Dai, Zhuxiang & Song, Gongfei & Du, Haiping, 2019. "Simultaneous disturbance estimation and fault reconstruction using probability density functions," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    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. Yang, Xilian & Zhao, Qunfei & Wang, Yuzhang & Cheng, Kanru, 2023. "Fault signal reconstruction for multi-sensors in gas turbine control systems based on prior knowledge from time series representation," Energy, Elsevier, vol. 262(PA).

    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. 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).
    2. Peng, Yanru & Xu, Shengyuan, 2023. "Adaptive tracking control for a class of stochastic nonlinear systems with full-state constraints and dead-zone," Applied Mathematics and Computation, Elsevier, vol. 452(C).
    3. Han, Jian & Liu, Xiuhua & Wei, Xinjiang & Zhang, Huifeng & Hu, Xin, 2021. "Adjustable dimension descriptor observer based fault estimation of nonlinear system with unknown input," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    4. Li, Tao & Zhang, Zhixuan & Dai, Zhuxiang & Xu, Liuyong, 2022. "Intermediate-estimator-based fault tolerant shape control via PDFs," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    5. 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).
    6. Zhang, Meijie & Yang, Xinsong & Xiang, Zhengrong & Liu, Xiaoyang, 2023. "Consensus of nonlinear MAS via double nonidentical mode-dependent event-triggered switching control," Applied Mathematics and Computation, Elsevier, vol. 453(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:399:y:2021:i:c:s0096300321000485. 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.