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Optimization of PID parameters for controlling DC motor based on the aquila optimizer algorithm

International Journal of Power Electronics and Drive Systems · Vol. 13 No. 1 (2022) · pp. 216–222

DOI
10.11591/ijpeds.v13.i1.pp216-222
ISSN
2722-256X, 2088-8694
Published
2022-03-01
Publisher
Institute of Advanced Engineering and Science
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This study presents the application of the aquila optimizer (AO) algorithm to determine the parameters of the proportional integral derivative (PID) controller to control the speed of a dc motor. The AO method is inspired by the most popular bird of prey in the northern hemisphere named Aquila. Initially, the proposed AO algorithm is applied to unimodal and multimodal benchmark optimization problems. To get the performance of the AO method, the controller is compared with other methods, namely Seagull optimization algorithm (SOA), marine predators algorithm, giza pyramids construction (GPC), and chimp optimization algorithm (ChOA). The results represent that the AO is promising and shows the effectiveness. Determination of PID parameters using the AO method for dc motor speed control system shows superior performance.

Keywords

Collaboration network of the authors

40 authors · 106 co-authorship links · 24 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Negeri Surabaya
  • Institut Teknologi Sepuluh Nopember
  • Al al-Bayt University
  • Nigerian Defence Academy
  • Universitas Halu Oleo
  • Universitas Airlangga
  • National Taiwan University of Science and Technology
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Ayusta Lukita WardaniUniversitas Negeri Surabaya6
Aditya PrapancaAffiliation unknown5
Laith AbualigahAl al-Bayt University4
Diego OlivaAffiliation unknown4
Reza RahmadianAffiliation unknown4
Mahendra WidyartonoAffiliation unknown4
Hisham A. ShehadehAffiliation unknown4
Unit Three KartiniUniversitas Negeri Surabaya4
Aliyu SaboNigerian Defence Academy3
Supari MuslimAffiliation unknown3
Abeer AljohaniAffiliation unknown3
Joko JokoUniversitas Halu Oleo3
Heri SuryoatmojoInstitut Teknologi Sepuluh Nopember2
Feby Agung PamujiInstitut Teknologi Sepuluh Nopember2
Aditya Chandra HermawanAffiliation unknown2
Nur Vidia Laksmi B.Universitas Negeri Surabaya1
Muhammad Syahril MubarokUniversitas Airlangga1
Moh. Zaenal EffendiAffiliation unknown1
Tian‐Hua LiuNational Taiwan University of Science and Technology1
Diego A. OlivaUniversidad de Guadalajara1
Abeer A. AljohaniTaibah University1
Satria PinanditaAffiliation unknown1
Andhy Tri AdriyantoAffiliation unknown1
Yuliyanto Budi SetiawanAffiliation unknown1
Sri AnggraeniAffiliation unknown1
Ismail FadlurrohmanAffiliation unknown1
Riandi RiandiIndonesia University of Education1
Anna ArgiyantiAffiliation unknown1
Widya CristantiAffiliation unknown1
Ridho Ilafi SukmaAffiliation unknown1
Charis Fathul HadiAffiliation unknown1
Agus Budi SantosaAffiliation unknown1
Toufik MziliChouaib Doukkali University1
Muhammad ZainuriDiponegoro University1
Iis Widya HarmokoAffiliation unknown1
Anindya WirasatriyaAffiliation unknown1
Sudibyakto SudibyaktoAffiliation unknown1

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.

Metadata source: OAI-PMH (metadata jurnal) http://ijpeds.iaescore.com/index.php/IJPEDS/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Optimization of PID parameters for controlling DC motor based on the aquila optimizer algorithm</dc:title>
	<dc:creator>Aribowo, Widi</dc:creator>
	<dc:creator>Supari, Supari</dc:creator>
	<dc:creator>Suprianto, Bambang</dc:creator>
	<dc:subject xml:lang="en-US">aquila optimizer; artificial intelligence; DC motor; metaheuristic; proportional integral derivative</dc:subject>
	<dc:description xml:lang="en-US">This study presents the application of the aquila optimizer (AO) algorithm to determine the parameters of the proportional integral derivative (PID) controller to control the speed of a dc motor. The AO method is inspired by the most popular bird of prey in the northern hemisphere named Aquila. Initially, the proposed AO algorithm is applied to unimodal and multimodal benchmark optimization problems. To get the performance of the AO method, the controller is compared with other methods, namely Seagull optimization algorithm (SOA), marine predators algorithm, giza pyramids construction (GPC), and chimp optimization algorithm (ChOA). The results represent that the AO is promising and shows the effectiveness. Determination of PID parameters using the AO method for dc motor speed control system shows superior performance.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2022-03-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21766</dc:identifier>
	<dc:identifier>10.11591/ijpeds.v13.i1.pp216-222</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Power Electronics and Drive Systems (IJPEDS); Vol 13, No 1: March 2022; 216-222</dc:source>
	<dc:source>2722-256X</dc:source>
	<dc:source>2088-8694</dc:source>
	<dc:source>10.11591/ijpeds.v13.i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21766/13762</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Widi Aribowo, Supari Supari, Bambang Suprianto</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>