{"title":"非参数化非线性连续系统跟踪依赖迭代轨迹的自适应ILC方法","authors":"Yaohui Ding, Xiao-dong Li","doi":"10.1109/DDCLS52934.2021.9455650","DOIUrl":null,"url":null,"abstract":"This paper proposes an adaptive Iterative Learning Control (ILC) method for no-parameterized nonlinear continuous systems to track iteration-dependent reference trajectory. The adaptive ILC method releases the general requirement in adaptive ILC community that the control gain matrices of the plants are real asymmetric or even positive-definite. Under the iteration-dependent reference trajectory and unknown external disturbance, the proposed adaptive ILC controller with a simple structure, which includes only two iterative variables, is able to guarantee the convergence of ILC tracking errors. A numerical example is used to verify the effectiveness of the proposed Adaptive ILC method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Adaptive ILC Method for Non-Parameterized Nonlinear Continuous Systems to Track Iteration-Dependent Trajectory\",\"authors\":\"Yaohui Ding, Xiao-dong Li\",\"doi\":\"10.1109/DDCLS52934.2021.9455650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an adaptive Iterative Learning Control (ILC) method for no-parameterized nonlinear continuous systems to track iteration-dependent reference trajectory. The adaptive ILC method releases the general requirement in adaptive ILC community that the control gain matrices of the plants are real asymmetric or even positive-definite. Under the iteration-dependent reference trajectory and unknown external disturbance, the proposed adaptive ILC controller with a simple structure, which includes only two iterative variables, is able to guarantee the convergence of ILC tracking errors. A numerical example is used to verify the effectiveness of the proposed Adaptive ILC method.\",\"PeriodicalId\":325897,\"journal\":{\"name\":\"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DDCLS52934.2021.9455650\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS52934.2021.9455650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Adaptive ILC Method for Non-Parameterized Nonlinear Continuous Systems to Track Iteration-Dependent Trajectory
This paper proposes an adaptive Iterative Learning Control (ILC) method for no-parameterized nonlinear continuous systems to track iteration-dependent reference trajectory. The adaptive ILC method releases the general requirement in adaptive ILC community that the control gain matrices of the plants are real asymmetric or even positive-definite. Under the iteration-dependent reference trajectory and unknown external disturbance, the proposed adaptive ILC controller with a simple structure, which includes only two iterative variables, is able to guarantee the convergence of ILC tracking errors. A numerical example is used to verify the effectiveness of the proposed Adaptive ILC method.