DocumentCode
1163022
Title
On initial conditions in iterative learning control
Author
Xu, Jian-Xin ; Yan, Rui
Author_Institution
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Volume
50
Issue
9
fYear
2005
Firstpage
1349
Lastpage
1354
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.
Keywords
Lyapunov methods; adaptive control; convergence; iterative methods; learning systems; Lyapunov theory; boundedness property; initial resetting condition; iterative learning control; learning convergence; local Lipschitz nonlinearity; time-varying parametric uncertainty; Computer errors; Control nonlinearities; Control systems; Convergence; Iterative algorithms; Iterative methods; Robustness; System performance; Trajectory; Uncertainty; Initial conditions; iterative learning control (ILC); learning convergence;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2005.854613
Filename
1506941
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