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A Unified Analysis Tool in Iterative Learning Control: Composite Energy Function

机译:迭代学习控制中的统一分析工具:复合能量函数

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Usually, the convergence analysis of a continuous-time iterative learning control (ILC) algorithm is carried out by using either Contraction Mapping (CM) or Composite Energy Function (CEF) based methods. They are subtly different in terms of types of systems to which it can be applied, the convergence properties, convergence condition and the standing assumptions. Although the link between these two methods has been observed in literature, there is no clear statement to show that CEF-based method can be served as a unified analysis tool. This paper shows this fact by re-proving the well-known CM-based convergence results of P-type ILC algorithms using a novel CEF method.
机译:通常,通过使用基于收缩映射(CM)或基于复合能量功能(CEF)的方法来执行连续时间迭代学习控制(ILC)算法的收敛性分析。它们在可以应用的系统类型,收敛性,收敛条件和站立假设方面细巧不同。虽然在文献中观察到这两种方法之间的链接,但没有明确的陈述表明基于CEF的方法可以作为统一分析工具。本文通过使用新的CEF方法重新证明了P型ILC算法的众所周知的CM基收敛结果来显示这一事实。

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