期刊
AUTOMATICA
卷 49, 期 5, 页码 1465-1472出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2013.02.008
关键词
Iterative learning control; Specified data points; Optimal tracking
资金
- National Research Foundation of Korea (NRF)
- Korea government (MEST) [2011-0021474]
- National Research Foundation of Korea [2011-0021474] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
In this paper, we present two iterative learning control (ILC) frameworks for tracking problems with specified data points that are desired points at certain time instants. To design ILC systems for such problems, unlike traditional ILC approaches, we first develop an algorithm in which not only the control signal but also the reference trajectory is updated at each trial. We investigate the relationship between the reference trajectory and ILC tracking control as it relates to the rate of convergence. Second, a new ILC scheme is proposed to produce output curves that pass close to the desired points. Here, the control signals are generated by solving an optimal ILC problem with respect to the desired sampling points. One of the key advantages of the proposed approaches is a significant reduction of the computational cost. (c) 2013 Elsevier Ltd. All rights reserved.
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