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Iterative learning control with feedback using Fourier series with application to robot trajectory tracking

Published online by Cambridge University Press:  09 March 2009

Jong-Woon Lee
Department of Electrical EngineeringKorea Advanced Institute of Science and Technology373–1 Kusong-dongYusong-ku, Taejeon, 305–701 (Korea)
Hak-Sung Lee
Department of Electrical EngineeringKorea Advanced Institute of Science and Technology373–1 Kusong-dongYusong-ku, Taejeon, 305–701 (Korea)
Zeungnam Bien
Department of Electrical EngineeringKorea Advanced Institute of Science and Technology373–1 Kusong-dongYusong-ku, Taejeon, 305–701 (Korea)


The Fourier series is employed to approximate the input/output (I/O) characteristics of a dynamic system and, based on the approximation, a new learning control algorithm is proposed in order to find iteratively the control input for tracking a desired trajectory. The use of the Fourier series approximation of I/O renders at least a couple of useful consequences: the frequency characteristics of the system can be used in the controller design and the reconstruction of the system states is not required. The convergence condition of the proposed algorithm is provided and the existence and uniqueness of the desired control input is discussed. The effectiveness of the proposed algorithm is illustrated by computer simulation for a robot trajectory tracking. It is shown that, by adding a feedback term in learning control algorithm, robustness and convergence speed can be improved.

Research Article
Copyright © Cambridge University Press 1993

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