4.7 Article

Unified iterative learning control for flexible structures with input constraints

期刊

AUTOMATICA
卷 96, 期 -, 页码 326-336

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2018.06.051

关键词

Flexible structure; Distributed parameter system; Boundary iterative learning control; Disturbance rejection; Input constraint

资金

  1. National Research Foundation
  2. Keppel Corporation
  3. National University of Singapore

向作者/读者索取更多资源

This paper proposes a unified framework of iterative learning control for typical flexible structures under spatiotemporally varying disturbances. Input constraints and the external disturbances are smoothly tackled through hyperbolic tangent functions. Boundary iterative learning control (BILC) laws are proposed to guarantee the learning convergence. The closed-loop systems can converge to zero along the iteration axis on the basis of time-weighted Lyapunov-Krasovskii-like composite energy functions (CEF). Simulations are implemented to illustrate the effectiveness of the proposed BILC schemes. (C) 2018 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据