Iterative Learning Control Robustness and Monotonic Convergence for
This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many
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Series Editors E.D. Sontag · M. Thoma · A. Isidori · J.H. van Schuppen
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Randomized Algorithms for Analysis and Control of Uncertain Systems Roberto Tempo, Giuseppe Calafiore and Fabrizio Dabbene Switched Linear Systems Zhendong Sun and Shuzhi S. Ge Subspace Methods for System Identification Tohru Katayama Digital Control Systems Ioan D. Landau and Gianluca Zito Multivariable Computer-controlled Systems Efim N. Rosenwasser and Bernhard P. Lampe Dissipative Systems Analysis and Control (Second edition) Bernard Brogliato, Rogelio Lozano, Bernhard Maschke and Olav Egeland Algebraic Methods for Nonlinear Control Systems (Second edition) Giuseppe Conte, Claude H. Moog and Anna Maria Perdon Polynomial and Rational Matrices Tadeusz Kaczorek Simulation-based Algorithms for Markov Decision Processes Hyeong Soo Chang, Michael C. Fu, Jiaqiao Hu and Steven I. Marcus
Hyo-Sung Ahn, Kevin L. Moore and YangQuan Chen
Iterative Learning Control Robustness and Monotonic Convergence for Interval Systems
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Hyo-Sung Ahn, PhD Department of Mechatronics Gwangju Institute of Science and Technology (GIST) Buk-gu, Gwangju 500-712 Korea
Kevin L. Moore, PhD, PE Division of Engineering Colorado School of Mines Golden, CO 80401 USA
YangQuan Chen, PhD Center for Self-organizing and Intelligent Systems Utah State University Logan, UT 84322-4160 USA
British Library Cataloguing in Publication Data Ahn, Hyo-Sung Iterative learning control : robustness and monotonic convergence for interval systems. - (Communications an
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