{"title":"A design framework for nonlinear iterative learning control and repetitive control: Applied to three mechatronic case studies","authors":"Leontine Aarnoudse , Alexey Pavlov , Tom Oomen","doi":"10.1016/j.conengprac.2024.105976","DOIUrl":null,"url":null,"abstract":"<div><p>Iterative learning control (ILC) and repetitive control (RC) can lead to high performance by attenuating repeating disturbances perfectly, yet these approaches may amplify non-repeating disturbances. The aim of this paper is to achieve both perfect, fast attenuation of repeating disturbances and limited amplification of non-repeating disturbances. This is achieved by including a deadzone nonlinearity in the learning filter, which distinguishes disturbances based on their different amplitudes to apply different learning gains. Convergence conditions for nonlinear ILC and RC are developed, which are used in combination with system measurements in a comprehensive design procedure. Experimental implementation demonstrates fast learning and small errors.</p></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0967066124001369/pdfft?md5=ada70ca66f66936a451cb2e51900c1ba&pid=1-s2.0-S0967066124001369-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering Practice","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967066124001369","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
Abstract
Iterative learning control (ILC) and repetitive control (RC) can lead to high performance by attenuating repeating disturbances perfectly, yet these approaches may amplify non-repeating disturbances. The aim of this paper is to achieve both perfect, fast attenuation of repeating disturbances and limited amplification of non-repeating disturbances. This is achieved by including a deadzone nonlinearity in the learning filter, which distinguishes disturbances based on their different amplitudes to apply different learning gains. Convergence conditions for nonlinear ILC and RC are developed, which are used in combination with system measurements in a comprehensive design procedure. Experimental implementation demonstrates fast learning and small errors.
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.
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