Sand cat swarm optimization for controlling PID in DC motor
In this article, the direct current (DC) motor control approach is presented using the sand cat swarm optimization (SCSO) method to obtain the best proportional integral derivative (PID) parameters. DC motors are popular equipment. In addition, DC motors are easy to apply. SCSO is a method that adop...
Gespeichert in:
Veröffentlicht in: | Telkomnika 2024-04, Vol.22 (2), p.462-470 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 470 |
---|---|
container_issue | 2 |
container_start_page | 462 |
container_title | Telkomnika |
container_volume | 22 |
creator | Aribowo, Widi Ghith, Ehab Saif Rahmadian, Reza Widyartono, Mahendra Lukita Wardani, Ayusta Prapanca, Aditya Laksmi B., Nur Vidia |
description | In this article, the direct current (DC) motor control approach is presented using the sand cat swarm optimization (SCSO) method to obtain the best proportional integral derivative (PID) parameters. DC motors are popular equipment. In addition, DC motors are easy to apply. SCSO is a method that adopts the desert cat's life in nature when searching for prey. This cat is able to detect low frequencies below 2 kHz and also has an extraordinary ability to dig for prey. This research was carried out using the MATLAB/Simulink application. To obtain the performance of the SCSO method, a comparison method was used, namely particle swarm optimization (PSO), gray wolf optimizer (GWO), whale optimization algorithm (WOA), and aquila optimizer (AO). From the results of the study, it was found that the settling time value and integral total weighted absolute value error (ITAE) value of the SCSO method were the best compared to other methods. |
doi_str_mv | 10.12928/telkomnika.v22i2.25630 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3048504582</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3048504582</sourcerecordid><originalsourceid>FETCH-LOGICAL-c146t-73c7b7b17746b4a6633190b81afd010ab32edd4e8ee19d593661c65fb43eff223</originalsourceid><addsrcrecordid>eNpFkF9LwzAAxIMoOOY-gwGfO_OvSYNPsukcDBTU55C2iWRrk5pkin566yZ4cNzLcQc_AC4xmmMiSXWdTbcLvXc7Pf8gxJE5KTlFJ2BCKCKFJJKeggnmkhaj0TmYpbRFowQipawm4OZZ-xY2OsP0qWMPw5Bd7751dsFDGyJsgs8xdJ3zb_BpvYTOw-UC9iGHeAHOrO6Smf3lFLze370sHorN42q9uN0UDWY8F4I2ohY1FoLxmmnOKcUS1RXWtkUY6ZoS07bMVMZg2ZaSco4bXtqaUWMtIXQKro67Qwzve5Oy2oZ99OOloohVJWJl9dsSx1YTQ0rRWDVE1-v4pTBSB1jqH5Y6wFIHWPQHH-Ff4g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3048504582</pqid></control><display><type>article</type><title>Sand cat swarm optimization for controlling PID in DC motor</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Aribowo, Widi ; Ghith, Ehab Saif ; Rahmadian, Reza ; Widyartono, Mahendra ; Lukita Wardani, Ayusta ; Prapanca, Aditya ; Laksmi B., Nur Vidia</creator><creatorcontrib>Aribowo, Widi ; Ghith, Ehab Saif ; Rahmadian, Reza ; Widyartono, Mahendra ; Lukita Wardani, Ayusta ; Prapanca, Aditya ; Laksmi B., Nur Vidia</creatorcontrib><description>In this article, the direct current (DC) motor control approach is presented using the sand cat swarm optimization (SCSO) method to obtain the best proportional integral derivative (PID) parameters. DC motors are popular equipment. In addition, DC motors are easy to apply. SCSO is a method that adopts the desert cat's life in nature when searching for prey. This cat is able to detect low frequencies below 2 kHz and also has an extraordinary ability to dig for prey. This research was carried out using the MATLAB/Simulink application. To obtain the performance of the SCSO method, a comparison method was used, namely particle swarm optimization (PSO), gray wolf optimizer (GWO), whale optimization algorithm (WOA), and aquila optimizer (AO). From the results of the study, it was found that the settling time value and integral total weighted absolute value error (ITAE) value of the SCSO method were the best compared to other methods.</description><identifier>ISSN: 1693-6930</identifier><identifier>EISSN: 2302-9293</identifier><identifier>DOI: 10.12928/telkomnika.v22i2.25630</identifier><language>eng</language><publisher>Yogyakarta: Ahmad Dahlan University</publisher><subject>Algorithms ; Cats ; D C motors ; Electric motors ; Exploitation ; Methods ; Optimization algorithms ; Particle swarm optimization ; Phase transitions ; Proportional integral derivative ; Wolves</subject><ispartof>Telkomnika, 2024-04, Vol.22 (2), p.462-470</ispartof><rights>2024. This work is published under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Aribowo, Widi</creatorcontrib><creatorcontrib>Ghith, Ehab Saif</creatorcontrib><creatorcontrib>Rahmadian, Reza</creatorcontrib><creatorcontrib>Widyartono, Mahendra</creatorcontrib><creatorcontrib>Lukita Wardani, Ayusta</creatorcontrib><creatorcontrib>Prapanca, Aditya</creatorcontrib><creatorcontrib>Laksmi B., Nur Vidia</creatorcontrib><title>Sand cat swarm optimization for controlling PID in DC motor</title><title>Telkomnika</title><description>In this article, the direct current (DC) motor control approach is presented using the sand cat swarm optimization (SCSO) method to obtain the best proportional integral derivative (PID) parameters. DC motors are popular equipment. In addition, DC motors are easy to apply. SCSO is a method that adopts the desert cat's life in nature when searching for prey. This cat is able to detect low frequencies below 2 kHz and also has an extraordinary ability to dig for prey. This research was carried out using the MATLAB/Simulink application. To obtain the performance of the SCSO method, a comparison method was used, namely particle swarm optimization (PSO), gray wolf optimizer (GWO), whale optimization algorithm (WOA), and aquila optimizer (AO). From the results of the study, it was found that the settling time value and integral total weighted absolute value error (ITAE) value of the SCSO method were the best compared to other methods.</description><subject>Algorithms</subject><subject>Cats</subject><subject>D C motors</subject><subject>Electric motors</subject><subject>Exploitation</subject><subject>Methods</subject><subject>Optimization algorithms</subject><subject>Particle swarm optimization</subject><subject>Phase transitions</subject><subject>Proportional integral derivative</subject><subject>Wolves</subject><issn>1693-6930</issn><issn>2302-9293</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpFkF9LwzAAxIMoOOY-gwGfO_OvSYNPsukcDBTU55C2iWRrk5pkin566yZ4cNzLcQc_AC4xmmMiSXWdTbcLvXc7Pf8gxJE5KTlFJ2BCKCKFJJKeggnmkhaj0TmYpbRFowQipawm4OZZ-xY2OsP0qWMPw5Bd7751dsFDGyJsgs8xdJ3zb_BpvYTOw-UC9iGHeAHOrO6Smf3lFLze370sHorN42q9uN0UDWY8F4I2ohY1FoLxmmnOKcUS1RXWtkUY6ZoS07bMVMZg2ZaSco4bXtqaUWMtIXQKro67Qwzve5Oy2oZ99OOloohVJWJl9dsSx1YTQ0rRWDVE1-v4pTBSB1jqH5Y6wFIHWPQHH-Ff4g</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Aribowo, Widi</creator><creator>Ghith, Ehab Saif</creator><creator>Rahmadian, Reza</creator><creator>Widyartono, Mahendra</creator><creator>Lukita Wardani, Ayusta</creator><creator>Prapanca, Aditya</creator><creator>Laksmi B., Nur Vidia</creator><general>Ahmad Dahlan University</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BVBZV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope></search><sort><creationdate>20240401</creationdate><title>Sand cat swarm optimization for controlling PID in DC motor</title><author>Aribowo, Widi ; Ghith, Ehab Saif ; Rahmadian, Reza ; Widyartono, Mahendra ; Lukita Wardani, Ayusta ; Prapanca, Aditya ; Laksmi B., Nur Vidia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c146t-73c7b7b17746b4a6633190b81afd010ab32edd4e8ee19d593661c65fb43eff223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Cats</topic><topic>D C motors</topic><topic>Electric motors</topic><topic>Exploitation</topic><topic>Methods</topic><topic>Optimization algorithms</topic><topic>Particle swarm optimization</topic><topic>Phase transitions</topic><topic>Proportional integral derivative</topic><topic>Wolves</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aribowo, Widi</creatorcontrib><creatorcontrib>Ghith, Ehab Saif</creatorcontrib><creatorcontrib>Rahmadian, Reza</creatorcontrib><creatorcontrib>Widyartono, Mahendra</creatorcontrib><creatorcontrib>Lukita Wardani, Ayusta</creatorcontrib><creatorcontrib>Prapanca, Aditya</creatorcontrib><creatorcontrib>Laksmi B., Nur Vidia</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>East & South Asia Database</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Telkomnika</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aribowo, Widi</au><au>Ghith, Ehab Saif</au><au>Rahmadian, Reza</au><au>Widyartono, Mahendra</au><au>Lukita Wardani, Ayusta</au><au>Prapanca, Aditya</au><au>Laksmi B., Nur Vidia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sand cat swarm optimization for controlling PID in DC motor</atitle><jtitle>Telkomnika</jtitle><date>2024-04-01</date><risdate>2024</risdate><volume>22</volume><issue>2</issue><spage>462</spage><epage>470</epage><pages>462-470</pages><issn>1693-6930</issn><eissn>2302-9293</eissn><abstract>In this article, the direct current (DC) motor control approach is presented using the sand cat swarm optimization (SCSO) method to obtain the best proportional integral derivative (PID) parameters. DC motors are popular equipment. In addition, DC motors are easy to apply. SCSO is a method that adopts the desert cat's life in nature when searching for prey. This cat is able to detect low frequencies below 2 kHz and also has an extraordinary ability to dig for prey. This research was carried out using the MATLAB/Simulink application. To obtain the performance of the SCSO method, a comparison method was used, namely particle swarm optimization (PSO), gray wolf optimizer (GWO), whale optimization algorithm (WOA), and aquila optimizer (AO). From the results of the study, it was found that the settling time value and integral total weighted absolute value error (ITAE) value of the SCSO method were the best compared to other methods.</abstract><cop>Yogyakarta</cop><pub>Ahmad Dahlan University</pub><doi>10.12928/telkomnika.v22i2.25630</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1693-6930 |
ispartof | Telkomnika, 2024-04, Vol.22 (2), p.462-470 |
issn | 1693-6930 2302-9293 |
language | eng |
recordid | cdi_proquest_journals_3048504582 |
source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
subjects | Algorithms Cats D C motors Electric motors Exploitation Methods Optimization algorithms Particle swarm optimization Phase transitions Proportional integral derivative Wolves |
title | Sand cat swarm optimization for controlling PID in DC motor |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-14T07%3A58%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Sand%20cat%20swarm%20optimization%20for%20controlling%20PID%20in%20DC%20motor&rft.jtitle=Telkomnika&rft.au=Aribowo,%20Widi&rft.date=2024-04-01&rft.volume=22&rft.issue=2&rft.spage=462&rft.epage=470&rft.pages=462-470&rft.issn=1693-6930&rft.eissn=2302-9293&rft_id=info:doi/10.12928/telkomnika.v22i2.25630&rft_dat=%3Cproquest_cross%3E3048504582%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3048504582&rft_id=info:pmid/&rfr_iscdi=true |