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
Link To Document :
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