Rückwald, TobiasTobiasRückwaldDrücker, SvenjaSvenjaDrückerDücker, Daniel-AndréDaniel-AndréDückerSeifried, RobertRobertSeifried2021-11-112021-11-112021-01-25Proceedings in applied mathematics and mechanics 20 (1) : e202000036 (2021)http://hdl.handle.net/11420/10884Usually, 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.en1617-7061Proceedings in applied mathematics and mechanics20211Wiley-VCHhttps://creativecommons.org/licenses/by-nc-nd/4.0/TechnikIngenieurwissenschaftenNonlinear system identification of a furuta pendulum using machine learning techniquesConference Paper10.15480/882.390310.1002/pamm.20200003610.15480/882.3903Conference Paper