Please use this identifier to cite or link to this item: https://doi.org/10.1109/TAC.2005.854613
Title: On initial conditions in iterative learning control
Authors: Xu, J.-X. 
Yan, R.
Keywords: Initial conditions
Iterative learning control (ILC)
Learning convergence
Issue Date: Sep-2005
Source: Xu, J.-X., Yan, R. (2005-09). On initial conditions in iterative learning control. IEEE Transactions on Automatic Control 50 (9) : 1349-1354. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2005.854613
Abstract: Initial conditions, or initial resetting conditions, play a fundamental role in all kinds of iterative learning control methods. In this note, we study five different initial conditions, disclose the inherent relationship between each initial condition and corresponding learning convergence (or boundedness) property. The iterative learning control method under consideration is based on Lyapunov theory, which is suitable for plants with time-varying parametric uncertainties and local Lipschitz nonlinearities. © 2005 IEEE.
Source Title: IEEE Transactions on Automatic Control
URI: http://scholarbank.nus.edu.sg/handle/10635/56869
ISSN: 00189286
DOI: 10.1109/TAC.2005.854613
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