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Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems

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This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.

248 pages, Hardcover

First published June 26, 2007

About the author

Hyo-Sung Ahn

10 books

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