Abstract
In this paper, for non-affine nonlinear system, a closed-loop PD-type iterative learning control algorithm with initial state learning is proposed and the sufficient condition for convergence is put forward. Using the contraction mapping method, it is proved that the output of the system with an arbitrary initial state can track the desired trajectory completely after iteration. The problem of convergence with initial state unknown is solved. The simulation results testify that the proposed algorithm is effective.
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© 2012 Springer-Verlag Berlin Heidelberg
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Bai, J., Yang, X., Wu, J. (2012). Iterative Learning Control with Initial State Learning for Non-affine Nonlinear System. In: Deng, W. (eds) Future Control and Automation. Lecture Notes in Electrical Engineering, vol 173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31003-4_26
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DOI: https://doi.org/10.1007/978-3-642-31003-4_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31002-7
Online ISBN: 978-3-642-31003-4
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