Suppressing intersample behavior in iterative learning control

doi:10.1016/j.automatica.2008.10.022

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Suppressing intersample behavior in iterative learning control

2009-04-01

Tom Oomen *

Jeroen van de Wijdeven

DOI：10.1016/j.automatica.2008.10.022

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Abstract

En 中文

Iterative Learning Control (ILC) is a control strategy to improve the performance of digital batch repetitive processes. Due to its digital implementation, discrete time ILC approaches do not guarantee good intersample behavior. In fact, common discrete time ILC approaches may deteriorate the intersample behavior, thereby reducing the performance of the sampled-data system. In this paper, a generally applicable multirate ILC approach is presented that enables to balance the at-sample performance and the intersample behavior. Furthermore, key theoretical issues regarding multirate systems are addressed, including the time-varying nature of the multirate ILC setup. The proposed multirate ILC approach is shown to outperform discrete time ILC in realistic simulation examples. (C) 2008 Elsevier Ltd. All rights reserved.

Keywords:

Learning control

Iterative

Sampled-data control

Sampled signals

Optimal control

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