实践中的学习控制:工业应用的新范例

2018 IEEE Conference on Control Technology and Applications (CCTA) Pub Date : 2018-08-01 DOI:10.1109/CCTA.2018.8511491

Jeroen Willems, E. Hostens, B. Depraetere, A. Steinhauser, J. Swevers

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引用次数: 5

摘要

本文针对实践中存在的学习控制问题提出了一些解决方案。我们使用RoFALT，这是一种免费的、基于模型的非线性系统迭代学习控制(ILC)工具，它实现了基于优化的两步方法。我们用概念增强它，以提高鲁棒性，收敛速度，并避免高计算负载在线。这些概念都说明了机电设置与滑块曲柄机构。

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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Learning Control in Practice: Novel Paradigms for Industrial Applications

This paper presents a number of solutions to issues with learning control in practice. We use RoFALT, a freely-available, model-based iterative learning control (ILC) tool for nonlinear systems, which implements an optimization-based two-step approach. We augment it with concepts to improve robustness, convergence speed, and avoid high computational loads online. These concepts are illustrated on an electromechanical set-up with slider-crank mechanism.

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来源期刊

2018 IEEE Conference on Control Technology and Applications (CCTA)

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