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
- National Research Foundation
- Keppel Corporation
- National University of Singapore
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.
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