基于q -学习的自适应PID球梁控制

Brilian Putra Amiruddin, R. E. A. Kadir
{"title":"基于q -学习的自适应PID球梁控制","authors":"Brilian Putra Amiruddin, R. E. A. Kadir","doi":"10.23919/EECSI50503.2020.9251898","DOIUrl":null,"url":null,"abstract":"The ball and beam system is one of the most used systems for benchmarking the controller response because it has nonlinear and unstable characteristics. Furthermore, in line with the increasing of computation power availability and artificial intelligence research intensity, especially the reinforcement learning field, nowadays plenty of researchers are working on a learning control approach for controlling systems. Due to that, in this paper, the adaptive PID controller based on Q-Learning (Q-PID) was used to control the ball position on the ball and beam system. From the simulation result, Q-PID outperforms the conventional PID and heuristic PID controller technique with the swifter settling time and lower overshoot percentage.","PeriodicalId":6743,"journal":{"name":"2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI)","volume":"18 1","pages":"203-208"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ball and Beam Control using Adaptive PID based on Q-Learning\",\"authors\":\"Brilian Putra Amiruddin, R. E. A. Kadir\",\"doi\":\"10.23919/EECSI50503.2020.9251898\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ball and beam system is one of the most used systems for benchmarking the controller response because it has nonlinear and unstable characteristics. Furthermore, in line with the increasing of computation power availability and artificial intelligence research intensity, especially the reinforcement learning field, nowadays plenty of researchers are working on a learning control approach for controlling systems. Due to that, in this paper, the adaptive PID controller based on Q-Learning (Q-PID) was used to control the ball position on the ball and beam system. From the simulation result, Q-PID outperforms the conventional PID and heuristic PID controller technique with the swifter settling time and lower overshoot percentage.\",\"PeriodicalId\":6743,\"journal\":{\"name\":\"2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI)\",\"volume\":\"18 1\",\"pages\":\"203-208\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/EECSI50503.2020.9251898\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/EECSI50503.2020.9251898","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

球梁系统具有非线性和不稳定的特性,是常用的控制器响应基准测试系统之一。此外,随着计算能力可用性的提高和人工智能研究的强度,特别是强化学习领域的研究,目前大量的研究人员正在研究控制系统的学习控制方法。为此,本文采用基于Q-Learning的自适应PID控制器(Q-PID)对球梁系统的球位置进行控制。仿真结果表明,Q-PID控制具有更快的稳定时间和更低的超调率,优于传统PID和启发式PID控制技术。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Ball and Beam Control using Adaptive PID based on Q-Learning
The ball and beam system is one of the most used systems for benchmarking the controller response because it has nonlinear and unstable characteristics. Furthermore, in line with the increasing of computation power availability and artificial intelligence research intensity, especially the reinforcement learning field, nowadays plenty of researchers are working on a learning control approach for controlling systems. Due to that, in this paper, the adaptive PID controller based on Q-Learning (Q-PID) was used to control the ball position on the ball and beam system. From the simulation result, Q-PID outperforms the conventional PID and heuristic PID controller technique with the swifter settling time and lower overshoot percentage.
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
自引率
0.00%
发文量
0
期刊最新文献
Aquatic Iguana: A Floating Waste Collecting Robot with IoT Based Water Monitoring System Improving the Anomaly Detection by Combining PSO Search Methods and J48 Algorithm A Wireless ECG Device with Mobile Applications for Android Features Extraction on IoT Intrusion Detection System Using Principal Components Analysis (PCA) Deep Convolutional Architecture for Block-Based Classification of Small Pulmonary Nodules
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1