Computation of maximum hands-off control

Takuya Ikeda, M. Nagahara
{"title":"Computation of maximum hands-off control","authors":"Takuya Ikeda, M. Nagahara","doi":"10.1109/SICEISCS.2016.7470166","DOIUrl":null,"url":null,"abstract":"Maximum hands-off control is a control that has the minimum L0 norm among all feasible controls. So far, we have proved that the maximum hands-off control is equivalent to the L1-optimal control under the normality assumption and is in general equivalent to the Lp-optimal control with 0 <; p <; 1. In this paper, by utilizing these results we give a numerical optimization method for the maximum hands-off control. We adopt a time discretization approach. As the complexity of the approximated problem then grows exponentially, we instead solve the equivalent L1 or Lp-optimization. Under the normality assumption we apply the alternating direction method of multipliers (ADMM) for the maximum hands-off control, and otherwise we apply the successive linearization algorithm (SLA).","PeriodicalId":371251,"journal":{"name":"2016 SICE International Symposium on Control Systems (ISCS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 SICE International Symposium on Control Systems (ISCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SICEISCS.2016.7470166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Maximum hands-off control is a control that has the minimum L0 norm among all feasible controls. So far, we have proved that the maximum hands-off control is equivalent to the L1-optimal control under the normality assumption and is in general equivalent to the Lp-optimal control with 0 <; p <; 1. In this paper, by utilizing these results we give a numerical optimization method for the maximum hands-off control. We adopt a time discretization approach. As the complexity of the approximated problem then grows exponentially, we instead solve the equivalent L1 or Lp-optimization. Under the normality assumption we apply the alternating direction method of multipliers (ADMM) for the maximum hands-off control, and otherwise we apply the successive linearization algorithm (SLA).
最大不干涉控制的计算
最大不干涉控制是所有可行控制中L0规范最小的控制。至此,我们证明了最大不干涉控制等价于正态性假设下的l1最优控制,一般等价于0 <的lp最优控制;p <;1. 在本文中,利用这些结果,我们给出了最大不干涉控制的数值优化方法。我们采用时间离散化方法。随着近似问题的复杂性呈指数增长,我们转而解决等效的L1或lp优化。在正态性假设下,采用乘法器交替方向法(ADMM)进行最大不干涉控制,否则采用连续线性化算法(SLA)。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信