Title
Robust iterative learning control for a class of nonlinear systems
Keywords
Iterative learning control; Mult-input multi-output system; Robust nonlinear control
Abstract
A novel nonlinear control scheme - robust iterative learning control (RILC) is developed in this paper. The new robust ILC system provides a general framework targeting at synthesizing learning control and robust control methods with the help of Lyapunov's direct method, thereafter being able to handle more general classes of nonlinear uncertain systems. In the proposed control scheme, learning control and variable structure control are made to function in a complementary manner. The nonlinear learning control strategy is applied directly to the structured system uncertainties which can be separated and expressed as products of unknown state-independent functions and known state-dependent functions. For non-structured system uncertainties associated with known bounding functions as the only a priori knowledge, variable structure control (VSC) strategy is applied to ensure the global asymptotic stability. In addition, important issues regarding the objective trajectory categories, resetting condition, derivative signal requirement and their relationships have been made clear in this paper. © 1998 Elsevier Science Ltd. All rights reserved.
Publication Date
1-1-1998
Publication Title
Automatica
Volume
34
Issue
8
Number of Pages
983-988
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/S0005-1098(98)00036-3
Copyright Status
Unknown
Socpus ID
0032137219 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0032137219
STARS Citation
Xu, Jian Xin and Qu, Zhihua, "Robust iterative learning control for a class of nonlinear systems" (1998). Scopus Export 1990s. 3338.
https://stars.library.ucf.edu/scopus1990/3338