Please use this identifier to cite or link to this item: https://doi.org/10.1109/TSMCB.2003.818433
Title: On Iterative Learning from Different Tracking Tasks in the Presence of Time-Varying Uncertainties
Authors: Xu, J.-X. 
Xu, J. 
Keywords: Composite energy function
Iterative learning
Nonidentical trajectories
Nonlinear dynamics
Time-varying parametric uncertainty
Issue Date: Feb-2004
Citation: Xu, J.-X., Xu, J. (2004-02). On Iterative Learning from Different Tracking Tasks in the Presence of Time-Varying Uncertainties. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34 (1) : 589-597. ScholarBank@NUS Repository. https://doi.org/10.1109/TSMCB.2003.818433
Abstract: In this paper, we introduce a new iterative learning control (ILC) method, which enables learning from different tracking control tasks. The proposed method overcomes the limitation of traditional ILC in that, the target trajectories of any two consecutive iterations can be completely different. For nonlinear systems with time-varying and time-invariant parametric uncertainties, the new learning method works effectively to nullify the tracking error. To facilitate the learning control system design and analysis, in the paper we use a composite energy function (CEF) index, which consists of a positive scalar function and ℒ 2 norm of the function approximation error.
Source Title: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
URI: http://scholarbank.nus.edu.sg/handle/10635/82810
ISSN: 10834419
DOI: 10.1109/TSMCB.2003.818433
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

159
checked on Nov 12, 2018

WEB OF SCIENCETM
Citations

124
checked on Oct 17, 2018

Page view(s)

22
checked on Oct 26, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.