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Nonlinear system identification of a furuta pendulum using machine learning techniques
Citation Link: https://doi.org/10.15480/882.3903
Publikationstyp
Conference Paper
Date Issued
2021-01-25
Sprache
English
Author(s)
Institut
TORE-DOI
Volume
20
Issue
1
Article Number
e202000036
Citation
Proceedings in applied mathematics and mechanics 20 (1) : e202000036 (2021)
Contribution to Conference
Publisher DOI
Publisher
Wiley-VCH
Peer Reviewed
true
Usually, dynamical systems can be described by differential equations. An accurate model is essential when designing and optimizing a controller. However, not every system can be modeled easily by physical models due to highly nonlinear behavior, such as friction or backlash. Then, a data based approach, such as machine learning, might be helpful. The focus in this work is set on modeling dynamical systems using neural networks and deep learning, which are growing subjects in research and industry to identify nonlinear dynamics.
DDC Class
600: Technik
620: Ingenieurwissenschaften
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