Title
Feedforward motion control: From batch-to-batch learning to online parameter estimation
Author
Mooren, N.
Witvoet, G.
Oomen, T.
Publication year
2019
Abstract
Feedforward control is essential in highperformance 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.
Subject
High Tech Systems & Materials
Industrial Innovation
To reference this document use:
http://resolver.tudelft.nl/uuid:58d40f63-18b2-41b7-825b-6177c46c65ab
TNO identifier
869400
Publisher
Institute of Electrical and Electronics Engineers IEEE
ISSN
7431-619
Source
Proceedings of the American Control Conference, ACC 2019, 10-12 July 2019, Philadelphoa, PA, USA, 947-952
Article number
8814481
Document type
conference paper