论文标题
迭代学习控制 - 深度潜水
Iterative Learning Control -- Deep Dive
论文作者
论文摘要
可以通过直接迭代各种输入的方程来评估迭代学习控制器（ILC）的稳定性和收敛性，或者通过找到迭代系统的特征值，或形成Z传输和应用极点--零或等效的根端来评估。两个经常使用的标准是（i）差异矢量的渐近收敛（AC），以及（ii）矢量规范的单调收敛（MC）。后者（MC）的Z域对应物。在本文中，我们将所有三种方法和两种收敛测试应用于带有ILC包装器的简单工厂。使用一，两届学习功能。然后，我们可以提出问题：所有测试是否有效，他们是否同意稳定性？
The stability and convergence of an Iterative Learning Controller (ILC) may be assessed either by directly iterating the equations for a variety of inputs, or by finding the eigenvalues of the iterated system, or by forming the Z-transform and applying pole-zero or equivalent root locus. Two often-used criteria are (i) Asymptotic Convergence (AC) of the difference vectors, and (ii) mono-tonic convergence (MC) of the vector norm. The latter (MC) has a Z- domain counterpart. In this paper we apply all three methods and both convergence tests to a simple plant with an ILC wrapper. One, two and three-term learning functions are used. We can then ask the questions: do all the tests work, and do they agree on the stability?
