在有限时间 ILC 中提高性能和任务灵活性的频域方法

IF 2.5 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control Pub Date : 2024-11-01 DOI:10.1016/j.ejcon.2024.101033

Max van Haren , Kentaro Tsurumoto , Masahiro Mae , Lennart Blanken , Wataru Ohnishi , Tom Oomen

{"title":"在有限时间 ILC 中提高性能和任务灵活性的频域方法","authors":"Max van Haren , Kentaro Tsurumoto , Masahiro Mae , Lennart Blanken , Wataru Ohnishi , Tom Oomen","doi":"10.1016/j.ejcon.2024.101033","DOIUrl":null,"url":null,"abstract":"<div><div>Iterative learning control (ILC) techniques are capable of improving the tracking performance of control systems that repeatedly perform similar tasks by utilizing data from past iterations. The aim of this paper is to achieve both the task flexibility enabled by ILC with basis functions and the performance of frequency-domain ILC, with an intuitive design procedure. The cost function of norm-optimal ILC is determined that recovers frequency-domain ILC, and consequently, the feedforward signal is parameterized in terms of basis functions and frequency-domain ILC. The resulting method has the performance and design procedure of frequency-domain ILC and the task flexibility of basis functions ILC, and are complimentary to each other. Validation on a benchmark example confirms the capabilities of the framework.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101033"},"PeriodicalIF":2.5000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A frequency-domain approach for enhanced performance and task flexibility in finite-time ILC\",\"authors\":\"Max van Haren , Kentaro Tsurumoto , Masahiro Mae , Lennart Blanken , Wataru Ohnishi , Tom Oomen\",\"doi\":\"10.1016/j.ejcon.2024.101033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Iterative learning control (ILC) techniques are capable of improving the tracking performance of control systems that repeatedly perform similar tasks by utilizing data from past iterations. The aim of this paper is to achieve both the task flexibility enabled by ILC with basis functions and the performance of frequency-domain ILC, with an intuitive design procedure. The cost function of norm-optimal ILC is determined that recovers frequency-domain ILC, and consequently, the feedforward signal is parameterized in terms of basis functions and frequency-domain ILC. The resulting method has the performance and design procedure of frequency-domain ILC and the task flexibility of basis functions ILC, and are complimentary to each other. Validation on a benchmark example confirms the capabilities of the framework.</div></div>\",\"PeriodicalId\":50489,\"journal\":{\"name\":\"European Journal of Control\",\"volume\":\"80 \",\"pages\":\"Article 101033\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0947358024000931\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Control","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0947358024000931","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}

引用次数: 0

摘要

迭代学习控制（ILC）技术能够利用过去迭代的数据，改善重复执行类似任务的控制系统的跟踪性能。本文的目的是通过直观的设计程序，实现基函数 ILC 的任务灵活性和频域 ILC 的性能。本文确定了能恢复频域 ILC 的规范最优 ILC 成本函数，并因此根据基函数和频域 ILC 对前馈信号进行了参数化。由此产生的方法既有频域 ILC 的性能和设计程序，又有基函数 ILC 的任务灵活性，两者相得益彰。在一个基准实例上的验证证实了该框架的能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A frequency-domain approach for enhanced performance and task flexibility in finite-time ILC

Iterative learning control (ILC) techniques are capable of improving the tracking performance of control systems that repeatedly perform similar tasks by utilizing data from past iterations. The aim of this paper is to achieve both the task flexibility enabled by ILC with basis functions and the performance of frequency-domain ILC, with an intuitive design procedure. The cost function of norm-optimal ILC is determined that recovers frequency-domain ILC, and consequently, the feedforward signal is parameterized in terms of basis functions and frequency-domain ILC. The resulting method has the performance and design procedure of frequency-domain ILC and the task flexibility of basis functions ILC, and are complimentary to each other. Validation on a benchmark example confirms the capabilities of the framework.

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

European Journal of Control 工程技术-自动化与控制系统

CiteScore

5.80

自引率

5.90%

发文量

131

审稿时长

1 months

期刊介绍： The European Control Association (EUCA) has among its objectives to promote the development of the discipline. Apart from the European Control Conferences, the European Journal of Control is the Association''s main channel for the dissemination of important contributions in the field. The aim of the Journal is to publish high quality papers on the theory and practice of control and systems engineering. The scope of the Journal will be wide and cover all aspects of the discipline including methodologies, techniques and applications. Research in control and systems engineering is necessary to develop new concepts and tools which enhance our understanding and improve our ability to design and implement high performance control systems. Submitted papers should stress the practical motivations and relevance of their results. The design and implementation of a successful control system requires the use of a range of techniques: Modelling Robustness Analysis Identification Optimization Control Law Design Numerical analysis Fault Detection, and so on.