Feedforward Motion Control: From Batch-to-Batch Learning to Online Parameter Estimation

被引：3

作者：

Mooren, Noud ^{[1
]}

Witvoet, Gert ^{[1
,2
]}

Oomen, Tom ^{[1
]}

机构：

[1] Eindhoven Univ Technol, Fac Mech Engn, Control Syst Technol Grp, NL-5600 MB Eindhoven, Netherlands

[2] TNO Tech Sci, Optomechatron Dept, NL-2628 CK Delft, Netherlands

来源：

2019 AMERICAN CONTROL CONFERENCE (ACC) | 2019年

关键词：

IDENTIFICATION; DESIGN;

D O I：

10.23919/acc.2019.8814481

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Feedforward control is essential in high-performance motion control. The aim of this paper is to develop a unified framework for automatic feedforward optimization from both batch-wise data sets as well as real-time data. A statistical analysis is employed to analyze the effect of noise, i.e., an iteration varying disturbance, on feedforward controller performance. This provides new insights, both potential advantages as well as possible hazards of real-time estimation are considered. Finally, a case study confirms and illustrates the results.

引用

页码：947 / 952

页数：6

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