Unified iterative learning control for flexible structures with input constraints. (October 2018)

• Record Type: Journal Article
• Authors: He, Wei; Meng, Tingting; He, Xiuyu; Ge, Shuzhi Sam
• Is Part Of: Automatica. Volume 96(2018)
• Page Start: 326
• Page End: 336
• Publication Date: 2018-10
• Subjects: Flexible structure -- Distributed parameter system -- Boundary iterative learning control -- Disturbance rejection -- Input constraint; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2018.06.051
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: 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.