{"title":"加速收敛的点对点ILC","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":"{\"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}","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}
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.