Internal model-based robust iterative learning control for uncertain LTI systems

Abdelhamid Tayebi, M. Zaremba
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引用次数: 25

Abstract

Investigates the combination of an iterative learning control (ILC) with an internal model control (IMC) for uncertain linear time-invariant (LTI) systems. The convergence of the iterative process is investigated and reformulated as a general robust control problem. For a certain choice of the IMC and ILC filters, we prove that the condition of convergence to zero of the iterative process is nothing but the robust performance condition of the IMC structure. Using the general robust control formulation, we propose a design procedure for the ILC-IMC filters using the /spl mu/-synthesis approach.
基于内模型的不确定LTI系统鲁棒迭代学习控制
研究了不确定线性时不变(LTI)系统的迭代学习控制(ILC)与内模控制(IMC)的结合。研究了迭代过程的收敛性,并将其重新表述为一般鲁棒控制问题。对于IMC和ILC滤波器的特定选择,我们证明了迭代过程收敛于零的条件无非是IMC结构的鲁棒性条件。利用一般鲁棒控制公式,我们提出了一种使用/spl mu/-合成方法的ILC-IMC滤波器的设计过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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