IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v365y2020ics0096300319306794.html
   My bibliography  Save this article

On the stabilization of nondeterministic finite automata via static output feedback

Author

Listed:
  • Zhang, Zhipeng
  • Xia, Chengyi
  • Chen, Zengqiang

Abstract

A nondeterministic finite automaton (NDFA) can exhibit an uncertain behavior in modeling and analysis, and its stabilization is viewed as an essential component of theoretical research. In this paper, we focused on the problem of static output feedback stabilization of NDFA under the framework of matrix semi-tensor product (matrix STP). First, the dynamics of Moore-type NDFA can be described as a discrete-time bilinear expression by a matrix-based modeling approach. Subsequently, equilibrium point and closed transition matrix of NDFA are introduced, and the corresponding computational formulas are given based on the new matrix expression. By utilizing the matrix STP approach, we can obtain the necessary and sufficient conditions to implement the static state output feedback stabilization for NDFA. Meanwhile, starting from the matrix STP, we designed a systematic procedure to seek the controller through an extended output feedback feasible event set. Finally, an illustrative example is provided to prove the efficacy of newly proposed method. Current results are conducive to better understand and devise the effective finite automata for discrete event systems.

Suggested Citation

  • Zhang, Zhipeng & Xia, Chengyi & Chen, Zengqiang, 2020. "On the stabilization of nondeterministic finite automata via static output feedback," Applied Mathematics and Computation, Elsevier, vol. 365(C).
    • Handle: RePEc:eee:apmaco:v:365:y:2020:i:c:s0096300319306794
    DOI: 10.1016/j.amc.2019.124687
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319306794
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2019.124687?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Du, Leihao & Zhang, Zhipeng & Xia, Chengyi, 2023. "A state-flipped approach to complete synchronization of Boolean networks," Applied Mathematics and Computation, Elsevier, vol. 443(C).
    2. Li, Xiaoyu & Jia, Danyang & Niu, Xiaotong & Liu, Chen & Zhu, Peican & Liu, Dujuan & Chu, Chen, 2022. "Ability-based asymmetrical fitness calculation promotes cooperation in spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 412(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:365:y:2020:i:c:s0096300319306794. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.