用于带预览的前馈控制的控制相关神经网络：应用于工业平板打印机

IF 1.8 Q3 AUTOMATION & CONTROL SYSTEMS

IFAC Journal of Systems and Control Pub Date : 2024-01-09 DOI:10.1016/j.ifacsc.2024.100241

Leontine Aarnoudse , Johan Kon , Wataru Ohnishi , Maurice Poot , Paul Tacx , Nard Strijbosch , Tom Oomen

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引用次数: 0

摘要

前馈控制的性能在很大程度上取决于其补偿可重现干扰的能力。本文旨在为用于前馈控制的人工神经网络（ANN）开发一个系统框架。该方法涉及三个方面：强调闭环控制目标的新标准；包含处理延迟和非最小相位动态的预览；以及使用迭代学习算法生成训练数据，以解决泛化误差问题。该方法通过在工业平板打印机上的模拟和实验进行了说明。

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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Control-relevant neural networks for feedforward control with preview: Applied to an industrial flatbed printer

The performance of feedforward control depends strongly on its ability to compensate for reproducible disturbances. The aim of this paper is to develop a systematic framework for artificial neural networks (ANN) for feedforward control. The method involves three aspects: a new criterion that emphasizes the closed-loop control objective, inclusion of preview to deal with delays and non-minimum phase dynamics, and enabling the use of an iterative learning algorithm to generate training data in view of addressing generalization errors. The approach is illustrated through simulations and experiments on an industrial flatbed printer.

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来源期刊

IFAC Journal of Systems and Control AUTOMATION & CONTROL SYSTEMS-

CiteScore

3.70

自引率

5.30%

发文量