{"title":"Point-to-point ILC with accelerated convergence","authors":"B. Chu, D. Owens, C. Freeman, Yanhong Liu","doi":"10.1109/DDCLS.2017.8068127","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel point-to-point iterative learning control (ILC) algorithm for high performance trajectory tracking applications. Based on a successive project formulation of the point-to-point ILC design problem, two point-to-point ILC design algorithms are derived: one algorithm reCovers the norm optimal point to point ILC algorithm with a desirable physical property of converging to the minimum norm (energy) solution, and the other one (interestingly) accelerates convergence speed which could lead to significant reduction in system configuration time/cost. Numerical results are provided to demonstrate the proposed algorithms' effectiveness.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th Data Driven Control and Learning Systems (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS.2017.8068127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a novel point-to-point iterative learning control (ILC) algorithm for high performance trajectory tracking applications. Based on a successive project formulation of the point-to-point ILC design problem, two point-to-point ILC design algorithms are derived: one algorithm reCovers the norm optimal point to point ILC algorithm with a desirable physical property of converging to the minimum norm (energy) solution, and the other one (interestingly) accelerates convergence speed which could lead to significant reduction in system configuration time/cost. Numerical results are provided to demonstrate the proposed algorithms' effectiveness.