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Model Predictive Control System Design for Boiler Turbine Process

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 5 No. 5 (2015)

DOI
10.11591/ijece.v5i5.pp1054-1061
ISSN
2088-8708, 2088-8708
Published
2015-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In the present work the control of boiler turbine process with three manipulated variables namely fuel flow valve position, steam control valve position and feed water flow valve position and three controlled variables namely drum pressure, output power and drum water level deviation [8] has been attempted using MPC technique. Boiler turbine process is very complex and nonlinear multivariable process. A linearized model obtained using Taylor series expansion around operating point has been used.

Collaboration network of the authors

3 authors · 3 co-authorship links · 2 across different organisations

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  • Graphic Era University
  • Graphic Era Hill University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Model Predictive Control System Design for Boiler Turbine Process</dc:title><dc:creator>Kumar Sunori, Sandeep</dc:creator><dc:creator>Kumar Juneja, Pradeep</dc:creator><dc:creator>Jain, Anamika Bhatia</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In the present work the control of boiler turbine process with three manipulated variables namely fuel flow valve position, steam control valve position and feed water flow valve position and three controlled variables namely drum pressure, output power and drum water level deviation [8] has been attempted using MPC technique. Boiler turbine process is very complex and nonlinear multivariable process. A linearized model obtained using Taylor series expansion around operating point has been used.&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2015-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v5i5.pp1054-1061</dc:identifier><dc:identifier>10.11591/ijece.v5i5.pp1054-1061</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 5 No 5 (2015); 1054</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/5726/4603</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>