Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Optimal tuning linear quadratic regulator for gas turbine by genetic algorithm using integral time absolute error

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 2 (2020)

DOI
10.11591/ijece.v10i2.pp1367-1375
ISSN
2088-8708, 2088-8708
Published
2020-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

For multiple input-multiple output (MIMO) systems, the most common control strategy is the linear quadratic regulator (LQR) which relies on state vector feedback. Despite this strategy gives very good result, it still has trial and error procedure to select the values of its weight matrices which plays a important role in reaching to the desiered system performance. In order to overcome this problem, the Genetic algorithm is used. The design of genetic algorithm based linear quadratic regulator (GA-LQR) utilized Integral time absolute error (ITAE) as a cost function for optimization. The propsed procedure is implemented on a linear model of gas turbine to control the generator spool’s speed and the output power.

Collaboration network of the authors

No co-authors found in Melola yet.

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>Optimal tuning linear quadratic regulator for gas turbine by genetic algorithm using integral time absolute error</dc:title><dc:creator>Ahmed, Jamal M.</dc:creator><dc:description>&lt;jats:p&gt;For multiple input-multiple output (MIMO) systems, the most common control strategy is the linear quadratic regulator (LQR) which relies on state vector feedback. Despite this strategy gives very good result, it still has trial and error procedure to select the values of its weight matrices which plays a important role in reaching to the desiered system performance. In order to overcome this problem, the Genetic algorithm is used. The design of genetic algorithm based linear quadratic regulator (GA-LQR) utilized Integral time absolute error (ITAE) as a cost function for optimization. The propsed procedure is implemented on a linear model of gas turbine to control the generator spool’s speed and the output power.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-04-01</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.v10i2.pp1367-1375</dc:identifier><dc:identifier>10.11591/ijece.v10i2.pp1367-1375</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 2 (2020); 1367</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/18362/pdf</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>