仿真实例说明闭环迭代学习律的有效性和快速性。
The simulation example verifies the effectiveness of closed-loop iterative learning control law.
型迭代学习控制律是迭代学习控制的一种主要学习律。
D-type iterative learning control (ILC) law is one of the main laws of ILC.
对非正则系统的迭代学习控制，需要采用高阶微分学习律。
And high order differential learning law must be adapted for irregular systems.
讨论了具有初态学习和任意初态两种情况下的迭代学习律的收敛性和鲁棒性问题。
Two learning laws with initial state learning and random initial states are proposed, and their convergence and robustness are proved.
实验结果表明：本文提出的迭代学习律，只需要根据参考信号及输入输出信号就能实现对参考信号的完全跟踪；
The simulation result shows that the proposed ILC can track the reference signal according to the reference signal and the input-output data;
实验结果表明：本文提出的迭代学习律，只需要根据参考信号及输入输出信号就能实现对参考信号的完全跟踪；
The simulation result shows that the proposed ILC can track the reference signal according to the reference signal and the input-output data;
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