Optimal Feedback Control of Power Systems Using Eigenstructure Assignment and Particle Swarm Optimization

IF 0.2 4区 工程技术 Q4 ENGINEERING, CIVIL Naval Engineers Journal Pub Date : 2011-03-01 DOI:10.1111/J.1559-3584.2010.00300.X
F. Ferrese, Q. Dong, N. Nataraj, S. Biswas
{"title":"Optimal Feedback Control of Power Systems Using Eigenstructure Assignment and Particle Swarm Optimization","authors":"F. Ferrese, Q. Dong, N. Nataraj, S. Biswas","doi":"10.1111/J.1559-3584.2010.00300.X","DOIUrl":null,"url":null,"abstract":"The US Navy has a continuing interest and investment in basic and applied research in the area of automation and control. The potential naval applications for this research are numerous and wide ranging. The need for advances in control and automation systems exists from missile defense, to shipboard auxiliary systems, to naval aircraft, and virtually everywhere in between. This research is performed in industry, academia, and in naval laboratories across the nation. This paper will detail particular research in control theory being performed in the area of automation and controls in the naval laboratories. A particle swarm optimization algorithm is used to manipulate the state and control weighting matrices of a linear quadratic regulator to achieve an optimal control for a desired eigenstructure. The algorithm is demonstrated on a nonlinear power system model, and is found to be highly effective in the stabilization of the system output performance, showing both rapid convergence and a closed loop eigenstructure very close to the specified eigenstructure.","PeriodicalId":49775,"journal":{"name":"Naval Engineers Journal","volume":"25 1","pages":"67-75"},"PeriodicalIF":0.2000,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Naval Engineers Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1111/J.1559-3584.2010.00300.X","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 1

Abstract

The US Navy has a continuing interest and investment in basic and applied research in the area of automation and control. The potential naval applications for this research are numerous and wide ranging. The need for advances in control and automation systems exists from missile defense, to shipboard auxiliary systems, to naval aircraft, and virtually everywhere in between. This research is performed in industry, academia, and in naval laboratories across the nation. This paper will detail particular research in control theory being performed in the area of automation and controls in the naval laboratories. A particle swarm optimization algorithm is used to manipulate the state and control weighting matrices of a linear quadratic regulator to achieve an optimal control for a desired eigenstructure. The algorithm is demonstrated on a nonlinear power system model, and is found to be highly effective in the stabilization of the system output performance, showing both rapid convergence and a closed loop eigenstructure very close to the specified eigenstructure.
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
基于特征结构分配和粒子群优化的电力系统最优反馈控制
美国海军对自动化和控制领域的基础和应用研究有着持续的兴趣和投资。这项研究的潜在海军应用是众多而广泛的。从导弹防御到舰载辅助系统,再到海军飞机,以及介于两者之间的几乎所有地方,对控制和自动化系统的进步的需求都存在。这项研究在全国各地的工业、学术界和海军实验室进行。本文将详细介绍海军实验室在自动化和控制领域进行的控制理论方面的具体研究。采用粒子群优化算法对线性二次型调节器的状态和控制权矩阵进行处理,以实现对期望特征结构的最优控制。在一个非线性电力系统模型上进行了验证,结果表明该算法对系统输出性能的稳定非常有效,收敛速度快,闭环特征结构与指定特征结构非常接近。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Naval Engineers Journal
Naval Engineers Journal 工程技术-工程:海洋
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊最新文献
Author's Response Author's Response Author's Response PRESIDENT'S PAGE THE FRANK G. LAW AWARD
×
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