Titlebook: Iterative Learning Control; Analysis, Design, In Zeungnam Bien,Jian-Xin Xu Book 1998 Springer Science+Business Media New York 1998 Nonlinea

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System Identification and Learning Control cannot be expected in practice, it is often sufficiently accurate in guiding the learning process to achieve a level of tracking accuracy beyond that obtained by inverting the identified model alone. Numerical and experimental results are used to illustrate key concepts described in this chapter.

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implicity and effectiveness, ILC has received considerable attention and applications in many areas for the past one and half decades. Most contributions have been focused on developing new ILC algorithms with property analysis. Since 1992, the research in ILC has progressed by leaps and bounds. On one hand, 978-1-4613-7575-3978-1-4615-5629-9

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Suguru Arimotorocess of development rather than as an interval-based add-on. For evaluation theory, it highlights a historical preoccupation with improving evaluation without assessing its inherent worth, and considers alternative ways to enhance the value of evaluation for small non-profits..978-3-030-58981-3978-3-030-58979-0

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Design of Quadratic Criterion-Based Iterative Learning Controlduction but also input moderation and robustness enhancement at a minimum expense of tracking performance..A separate algorithm minimizing the worst-case error for a convex, compact model set is developed and the convergence is established under mild assumptions..Numerical examples are provided to d