随机迭代反馈调整用于机电一体化系统的快速 MIMO 反馈设计

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice Pub Date : 2024-11-06 DOI:10.1016/j.conengprac.2024.106152

Leontine Aarnoudse , Peter den Toom , Tom Oomen

{"title":"随机迭代反馈调整用于机电一体化系统的快速 MIMO 反馈设计","authors":"Leontine Aarnoudse , Peter den Toom , Tom Oomen","doi":"10.1016/j.conengprac.2024.106152","DOIUrl":null,"url":null,"abstract":"<div><div>Iterative feedback tuning (IFT) enables the tuning of feedback controllers using only measured data to obtain the gradient of a cost criterion. The aim of this paper is to reduce the required number of experiments for MIMO IFT. It is shown that, through a randomization technique, an unbiased gradient estimate can be obtained from a single dedicated experiment, regardless of the size of the MIMO system. The gradient estimate is used in a stochastic gradient descent algorithm. The approach is experimentally validated on a mechatronic system, showing a significantly reduced number of experiments compared to standard IFT.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106152"},"PeriodicalIF":5.4000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Randomized iterative feedback tuning for fast MIMO feedback design of a mechatronic system\",\"authors\":\"Leontine Aarnoudse , Peter den Toom , Tom Oomen\",\"doi\":\"10.1016/j.conengprac.2024.106152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Iterative feedback tuning (IFT) enables the tuning of feedback controllers using only measured data to obtain the gradient of a cost criterion. The aim of this paper is to reduce the required number of experiments for MIMO IFT. It is shown that, through a randomization technique, an unbiased gradient estimate can be obtained from a single dedicated experiment, regardless of the size of the MIMO system. The gradient estimate is used in a stochastic gradient descent algorithm. The approach is experimentally validated on a mechatronic system, showing a significantly reduced number of experiments compared to standard IFT.</div></div>\",\"PeriodicalId\":50615,\"journal\":{\"name\":\"Control Engineering Practice\",\"volume\":\"154 \",\"pages\":\"Article 106152\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Control Engineering Practice\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0967066124003113\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering Practice","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967066124003113","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}

引用次数: 0

摘要

迭代反馈调谐（IFT）可以仅使用测量数据来获得成本准则的梯度，从而对反馈控制器进行调谐。本文旨在减少 MIMO IFT 所需的实验次数。研究表明，通过随机化技术，无论多输入多输出系统的规模如何，都能从一次专门实验中获得无偏梯度估计值。梯度估计值用于随机梯度下降算法。该方法在机电一体化系统上进行了实验验证，结果表明，与标准 IFT 相比，实验次数大大减少。

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

Randomized iterative feedback tuning for fast MIMO feedback design of a mechatronic system

Iterative feedback tuning (IFT) enables the tuning of feedback controllers using only measured data to obtain the gradient of a cost criterion. The aim of this paper is to reduce the required number of experiments for MIMO IFT. It is shown that, through a randomization technique, an unbiased gradient estimate can be obtained from a single dedicated experiment, regardless of the size of the MIMO system. The gradient estimate is used in a stochastic gradient descent algorithm. The approach is experimentally validated on a mechatronic system, showing a significantly reduced number of experiments compared to standard IFT.

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

Control Engineering Practice 工程技术-工程：电子与电气

CiteScore

9.20

自引率

12.20%

发文量

183

审稿时长

44 days

期刊介绍： Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper. The scope of Control Engineering Practice matches the activities of IFAC. Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.