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A survey on iterative learning control for nonlinear systems. (English) Zbl 1227.93053

Summary: In this article we review the recent advances in Iterative Learning Control (ILC) for nonlinear dynamic systems. In the research field of ILC, two categories of system nonlinearities are considered, namely, the Global Lipschitz Continuous (GLC) functions and Local Lipschitz Continuous (LLC) functions. ILC for GLC systems is widely studied and analyzed using contraction mapping approach, and the focus of recent exploration moves to application problems, though a number of theoretical issues remain open. ILC for LLC systems is currently a hot area and the recent research focuses on ILC design and analysis by means of Lyapunov’s approach. The objectives of this article are to introduce recent development and advances in nonlinear ILC schemes, highlight their effectiveness and limitations, as well as to discuss the directions for further exploration of nonlinear ILC.

MSC:

93C10 Nonlinear systems in control theory
68T05 Learning and adaptive systems in artificial intelligence
93-02 Research exposition (monographs, survey articles) pertaining to systems and control theory
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