TY - GEN
T1 - Convergence analysis of iterative learning control with uncertain initial conditions
AU - Fang, Yong
AU - Soh, Yeng Chai
AU - Feng, Gary G.
PY - 2002
Y1 - 2002
N2 - This paper explores convergence problem of iterative learning control (ILC) for linear discrete-time multivariable systems with uncertain initial conditions from two-dimensional (2-D) notion. The iterative learning process is described by a 2-D learning model, which includes both the system dynamics and the learning process. A simple ILC rule is used and the effect of tracking errors against varying initial conditions is investigated. Based on 2-D system theory, the conditions of the convergence of the learning control rules are proposed. It it shown that the learning rule can be guaranteed to converge with respect to small perturbations of the system parameters even though the initial condition of each iteration is variable.
AB - This paper explores convergence problem of iterative learning control (ILC) for linear discrete-time multivariable systems with uncertain initial conditions from two-dimensional (2-D) notion. The iterative learning process is described by a 2-D learning model, which includes both the system dynamics and the learning process. A simple ILC rule is used and the effect of tracking errors against varying initial conditions is investigated. Based on 2-D system theory, the conditions of the convergence of the learning control rules are proposed. It it shown that the learning rule can be guaranteed to converge with respect to small perturbations of the system parameters even though the initial condition of each iteration is variable.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0036945955&origin=recordpage
M3 - RGC 32 - Refereed conference paper (with host publication)
VL - 2
SP - 960
EP - 963
BT - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
T2 - Proceedings of the 4th World Congress on Intelligent Control and Automation
Y2 - 10 June 2002 through 14 June 2002
ER -