用于调整直流电机参数比例积分导数的新型改良瞪羚优化器

Q2 Mathematics Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI:10.11591/eei.v13i2.5575

Widi Aribowo, L. Abualigah, Diego Oliva, Aditya Prapanca

{"title":"用于调整直流电机参数比例积分导数的新型改良瞪羚优化器","authors":"Widi Aribowo, L. Abualigah, Diego Oliva, Aditya Prapanca","doi":"10.11591/eei.v13i2.5575","DOIUrl":null,"url":null,"abstract":"This article presents a modified method of mountain gazelle optimizer (MMGO) as a direct current (DC) motor control. Mountain gazelle optimizer (MGO) is an algorithm inspired by the life of the mountain gazelle animal in nature. This animal concept has five essential steps that are duplicated in mathematical modeling. This article uses two tests to get the performance of the MMGO method. The first test uses a benchmark function test with a comparison method, namely the sine tree seed algorithm (STSA) and the original MGO. The second test is the application of MMGO as a DC motor control. The simulation results show that MMGO can reduce the overshoot of conventional proportional integral derivative (PID) control by 0.447% and has a better integral time square error (ITSE) value of 5.345 than conventional PID control. Thus, the MMGO method shows promising performance.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel modified mountain gazelle optimizer for tuning parameter proportional integral derivative of DC motor\",\"authors\":\"Widi Aribowo, L. Abualigah, Diego Oliva, Aditya Prapanca\",\"doi\":\"10.11591/eei.v13i2.5575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a modified method of mountain gazelle optimizer (MMGO) as a direct current (DC) motor control. Mountain gazelle optimizer (MGO) is an algorithm inspired by the life of the mountain gazelle animal in nature. This animal concept has five essential steps that are duplicated in mathematical modeling. This article uses two tests to get the performance of the MMGO method. The first test uses a benchmark function test with a comparison method, namely the sine tree seed algorithm (STSA) and the original MGO. The second test is the application of MMGO as a DC motor control. The simulation results show that MMGO can reduce the overshoot of conventional proportional integral derivative (PID) control by 0.447% and has a better integral time square error (ITSE) value of 5.345 than conventional PID control. Thus, the MMGO method shows promising performance.\",\"PeriodicalId\":37619,\"journal\":{\"name\":\"Bulletin of Electrical Engineering and Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bulletin of Electrical Engineering and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11591/eei.v13i2.5575\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of Electrical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/eei.v13i2.5575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Mathematics","Score":null,"Total":0}

引用次数: 0

摘要

本文介绍了一种改进的山羚优化器（MMGO）方法，作为直流（DC）电机控制。山羚优化器（MGO）是一种算法，其灵感来源于大自然中山羚动物的生活。这种动物的概念有五个基本步骤，在数学建模中也有重复。本文通过两个测试来了解 MMGO 方法的性能。第一个测试使用基准函数测试与一种比较方法，即正弦树种子算法（STSA）和原始 MGO。第二个测试是将 MMGO 应用于直流电机控制。仿真结果表明，MMGO 可以将传统比例积分导数（PID）控制的过冲降低 0.447%，积分时间平方误差（ITSE）值为 5.345，优于传统 PID 控制。因此，MMGO 方法显示出良好的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

A novel modified mountain gazelle optimizer for tuning parameter proportional integral derivative of DC motor

This article presents a modified method of mountain gazelle optimizer (MMGO) as a direct current (DC) motor control. Mountain gazelle optimizer (MGO) is an algorithm inspired by the life of the mountain gazelle animal in nature. This animal concept has five essential steps that are duplicated in mathematical modeling. This article uses two tests to get the performance of the MMGO method. The first test uses a benchmark function test with a comparison method, namely the sine tree seed algorithm (STSA) and the original MGO. The second test is the application of MMGO as a DC motor control. The simulation results show that MMGO can reduce the overshoot of conventional proportional integral derivative (PID) control by 0.447% and has a better integral time square error (ITSE) value of 5.345 than conventional PID control. Thus, the MMGO method shows promising performance.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Bulletin of Electrical Engineering and Informatics Computer Science-Computer Science (miscellaneous)

CiteScore

3.60

自引率

0.00%

发文量

期刊介绍： Bulletin of Electrical Engineering and Informatics publishes original papers in the field of electrical, computer and informatics engineering which covers, but not limited to, the following scope: Computer Science, Computer Engineering and Informatics[...] Electronics[...] Electrical and Power Engineering[...] Telecommunication and Information Technology[...]Instrumentation and Control Engineering[...]