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Qing-Yuan Xu,Xiao-Dong Li,Mang-Mang Lv 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.2
Almost all of the existing research achievements in Iterative Learning Control (ILC) hitherto have beenfocused on One-Dimensional (1-D) dynamical systems. Few ILC researches are related to Two-Dimensional FornasiniMarchesina Model (2-D FMM). In this paper, an adaptive ILC approach is proposed for 2-D FMM systemwith non-repetitive reference trajectory under random boundary condition. The proposed adaptive ILC algorithmlearns the coefficient matrices of the system and updates the control input iteratively. As the times of iteration goesto infinity, the ILC tracking error outside the boundary tends to zero and all system signals keep bounded in thewhole ILC process. Illustrative examples are provided to verify the validity of the proposed adaptive ILC algorithm.