IDEAS home Printed from https://ideas.repec.org/a/hin/complx/5365493.html
   My bibliography  Save this article

Positiveness and Observer-Based Finite-Time Control for a Class of Markov Jump Systems with Some Complex Environment Parameters

Author

Listed:
  • Chengcheng Ren
  • Shuping He

Abstract

An observer-based finite-time - control law is devised for a class of positive Markov jump systems in a complex environment. The complex environment parameters include bounded uncertainties, unknown nonlinearities, and external disturbances. The objective is to devise an appropriate observer-based control law that makes the corresponding augment error dynamic Markov jump systems be positive and finite-time stabilizable and satisfy the given - disturbance attenuation index. A sufficient condition is initially established on the existence of the observer-based finite-time controller by using proper stochastic Lyapunov-Krasovskii functional. The design criteria are presented by means of linear matrix inequalities. Finally, the feasibility and validity of the main results can be illustrated through a numerical example.

Suggested Citation

  • Chengcheng Ren & Shuping He, 2018. "Positiveness and Observer-Based Finite-Time Control for a Class of Markov Jump Systems with Some Complex Environment Parameters," Complexity, Hindawi, vol. 2018, pages 1-13, November.
    • Handle: RePEc:hin:complx:5365493
    DOI: 10.1155/2018/5365493
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/5365493.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/5365493.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/5365493?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
    ---><---

    References listed on IDEAS

    as
    1. Chenguang Yang & Jing Na & Guang Li & Yanan Li & Junpei Zhong, 2018. "Neural Network for Complex Systems: Theory and Applications," Complexity, Hindawi, vol. 2018, pages 1-2, May.
    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.

      More about this item

      Statistics

      Access and download statistics

      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:hin:complx:5365493. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.