IDEAS home Printed from https://ideas.repec.org/a/hin/complx/5451439.html
   My bibliography  Save this article

Multivariable Model Reference Adaptive Control of an Industrial Power Boiler Using Recurrent RBFN

Author

Listed:
  • Jafar Tavoosi
  • Yavar Azarakhsh
  • Ardashir Mohammadzadeh
  • Saleh Mobayen
  • Jihad H. Asad
  • Rabia Safdar
  • Jesus Vega

Abstract

In industrial steam systems, the process requires a specific pressure, and the maximum permissible operating pressure is different. If the inlet steam pressure to the steam consuming equipment exceeds the operating pressure, it may cause hazards. Therefore, the more precise control of the boiler pressure is important. Since we are dealing with a nonlinear, time-varying, and multivariable system, the control method must be designed to handle this system well. Most of the methods proposed so far are either not physically feasible or the system has considered very simple. Therefore, in this paper, while modeling the boiler and its pressure relations more precisely, we will introduce a recurrent type-2 fuzzy RBFN-based model reference adaptive control system with various uncertainties so that the uncertainty and inaccuracy of the model can be compensated. The experimental results prove the efficiency of the proposed method in boiler control.

Suggested Citation

  • Jafar Tavoosi & Yavar Azarakhsh & Ardashir Mohammadzadeh & Saleh Mobayen & Jihad H. Asad & Rabia Safdar & Jesus Vega, 2021. "Multivariable Model Reference Adaptive Control of an Industrial Power Boiler Using Recurrent RBFN," Complexity, Hindawi, vol. 2021, pages 1-12, September.
    • Handle: RePEc:hin:complx:5451439
    DOI: 10.1155/2021/5451439
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2021/5451439.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/complexity/2021/5451439.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/5451439?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
    ---><---

    Citations

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


    Cited by:

    1. Wasim Jamshed & Rabia Safdar & Ameni Brahmia & Abdullah K. Alanazi & Hala M. Abo-Dief & Mohamed Rabea Eid, 2023. "Numerical Simulations of Environmental Energy Features in Solar Pump Application by Using Hybrid Nanofluid Flow: Prandtl-Eyring Case," Energy & Environment, , vol. 34(4), pages 780-807, June.

    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:5451439. 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: 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.