@article{22979,
  author       = {{Rüting, Arne Thorsten and Henke, Christian and Trächtler, Ansgar}},
  journal      = {{at-Automatisierungstechnik}},
  number       = {{4}},
  pages        = {{326–336}},
  title        = {{{Umsetzung einer echtzeitfähigen modellprädiktiven Trajektorienplanung für eine mehrachsige Hybridkinematik auf einer Industriesteuerung}}},
  volume       = {{67}},
  year         = {{2019}},
}

@inproceedings{22980,
  author       = {{Traphöner, Phillip and Olma, Simon and Kohlstedt, Andreas and Fast, Nikolai and Jäker, Karl-Peter and Trächtler, Ansgar}},
  booktitle    = {{8th IFAC Symposium on Mechatronic Systems}},
  title        = {{{Hardware-in-the-Loop Simulation for a Multiaxial Suspension Test Rig with a Nonlinear Spatial Vehicle Dynamics Model}}},
  year         = {{2019}},
}

@inproceedings{22981,
  author       = {{Traphöner, Phillip and Kohlstedt, Andreas and Olma, Simon and Jäker, Karl-Peter and Trächtler, Ansgar}},
  booktitle    = {{13. VDI/VDE Mechatronik-Tagung}},
  pages        = {{85--90}},
  publisher    = {{VDI-Verlag}},
  title        = {{{Hardware-in-the-Loop-Simulation einer Fahrzeugachse mit aktiver Wankstabilisierung mithilfe eines hydraulischen Hexapoden}}},
  year         = {{2019}},
}

@inbook{22982,
  author       = {{Rüddenklau, Nico and Biemelt, Patrick and Mertin, Sven and Gausemeier, Sandra and Trächtler, Ansgar}},
  booktitle    = {{IARIA SysMea}},
  pages        = {{72--88}},
  publisher    = {{IARIA}},
  title        = {{{Real-Time Lighting of High-Definition Headlamps for Night Driving Simulation}}},
  volume       = {{12}},
  year         = {{2019}},
}

@book{27116,
  author       = {{Gausemeier, Jürgen and Trächtler, Ansgar}},
  publisher    = {{Springer-Verlag GmbH}},
  title        = {{{Steigerung der Intelligenz mechatronischer Systeme}}},
  year         = {{2018}},
}

@misc{23419,
  author       = {{Tominski, Johannes and Zimmer, Detmar and Just, Viktor and Lankeit, Christopher and Oestersötebier, Felix and Trächtler, Ansgar}},
  title        = {{{Trainingsgerät mit Laufbandeinheit}}},
  year         = {{2018}},
}

@inbook{22984,
  author       = {{Lüke, Christopher and Timmermann, Julia and Kessler, Jan Henning and Trächtler, Ansgar}},
  booktitle    = {{Steigerung der Intelligenz mechatronischer Systeme}},
  pages        = {{153--192}},
  publisher    = {{Springer Vieweg}},
  title        = {{{Intelligente Steuerungen und Regelungen}}},
  volume       = {{1}},
  year         = {{2018}},
}

@book{22985,
  author       = {{Trächtler, Ansgar}},
  publisher    = {{Springer}},
  title        = {{{Ressourceneffiziente Selbstoptimierende Wäscherei}}},
  year         = {{2018}},
}

@inproceedings{22986,
  author       = {{Rüddenklau, Nico and Biemelt, Patrick and Henning, Sven and Gausemeier, Sandra and Trächtler, Ansgar}},
  booktitle    = {{SIMUL 2018, The Tenth International Conference on Advances in System Simulation}},
  publisher    = {{IARIA}},
  title        = {{{Shader-Based Realtime Simulation of High-Definition Automotive Headlamps}}},
  year         = {{2018}},
}

@inproceedings{22987,
  author       = {{Drüke, Simon and Bicker, Rainer and Schullter, Bernd and Henke, Christian and Trächtler, Ansgar}},
  booktitle    = {{Proceedings of the 10th International Conference on Rotor Dynamics - IFToMM. Vol. 2. International Conference on Rotor Dynamics - IFToMM}},
  pages        = {{383--397}},
  publisher    = {{Springer Nature Switzerland AG}},
  title        = {{{Rotordynamic instabilities in washing machines}}},
  year         = {{2018}},
}

@article{22988,
  author       = {{Gräler, Manuel and Springer, Robert and Henke, Christian and Trächtler, Ansgar and Homberg, Werner}},
  journal      = {{Swedish Production Symposium}},
  pages        = {{358--364}},
  title        = {{{Assisted setup of forming processes: compensation of initial stochastic disturbances}}},
  volume       = {{25}},
  year         = {{2018}},
}

@inproceedings{22989,
  author       = {{Rüting, Arne Thorsten and Henke, Christian and Trächtler, Ansgar}},
  booktitle    = {{EKA 2018 Entwurf komplexer Automatisierungssysteme - Beschreibungsmittel, Methoden, Werkzeuge und Anwendungen}},
  publisher    = {{IFAK - Institut für Automation und Kommunikation e.V.}},
  title        = {{{Umsetzung einer echtzeitfähigen Mehrgrößenoptimierung auf einer Industriesteuerung}}},
  year         = {{2018}},
}

@article{22990,
  author       = {{Springer, Robert and Graeler, Manuel and Homberg, Werner and Henke, Christian and Trächtler, Ansgar}},
  journal      = {{AIP Conference Proceedings}},
  number       = {{2018}},
  title        = {{{Model based Setup Assistant for Progressive Tools}}},
  volume       = {{160025}},
  year         = {{2018}},
}

@inproceedings{22992,
  author       = {{Henning, Sven and Biemelt, Patrick and Rüddenklau, Nico and Gausemeier, Sandra and Trächtler, Ansgar}},
  booktitle    = {{Proceedings of the DSC 2018 Europe VR: New trends in Human in the Loop simulation and testing. Driving simulation and VR}},
  pages        = {{91--98}},
  publisher    = {{Driving Simulation Association}},
  title        = {{{A Simulation Framework for Testing a Conceptual Hierarchical Autonomous Traffic Management System including an Intelligent External Traffic Simulation}}},
  year         = {{2018}},
}

@inproceedings{22994,
  author       = {{Lankeit, Christopher and Michael, Jan and Henke, Christian and Trächtler, Ansgar}},
  booktitle    = {{Proceedings 1st International Workshop on Learning from other Disciplines for Requirements Engineering}},
  pages        = {{4--7}},
  publisher    = {{IEEE}},
  title        = {{{Holistic Requirements for Interdisciplinary Development Processes}}},
  year         = {{2018}},
}

@article{22995,
  author       = {{Pai, Arathi and Riepold, Markus and Trächtler, Ansgar}},
  journal      = {{Mechatronics}},
  pages        = {{303--320}},
  title        = {{{Model-based precision position and force control of SMA actuators with a clamping application}}},
  volume       = {{50}},
  year         = {{2018}},
}

@article{22997,
  author       = {{Olma, Simon and Kohlstedt, Andreas and Traphöner, Phillip and Jäker, Karl-Peter and Trächtler, Ansgar}},
  journal      = {{Mechatronics}},
  pages        = {{212--224}},
  title        = {{{Observer-based nonlinear control strategies for Hardware-in-the-Loop simulations of multiaxial suspension test rigs}}},
  volume       = {{50}},
  year         = {{2018}},
}

@article{22998,
  author       = {{Holtkötter, Jens and Michael, Jan and Henke, Christian and Trächtler, Ansgar and Bockholt, Marcos and Möhlenkamp, Andreas and Katter, Michael}},
  journal      = {{Procedia Manufacturing}},
  pages        = {{235–242}},
  title        = {{{Rapid-Control-Prototyping as part of Model-Based Development of Heat Pump Dryers}}},
  volume       = {{24}},
  year         = {{2018}},
}

@inproceedings{23000,
  author       = {{Biemelt, Patrick and Henning, Sven and Rüddenklau, Nico and Gausemeier, Sandra and Trächtler, Ansgar}},
  booktitle    = {{Proceedings of the Driving Simulation Conference Europe VR (DSC)}},
  location     = {{Antibes, France}},
  pages        = {{79--85}},
  title        = {{{A Model Predictive Motion Cueing Strategy for a 5-Degree-of-Freedom Driving Simulator with Hybrid Kinematics}}},
  year         = {{2018}},
}

@article{22996,
  abstract     = {{The effective control design of a dynamical system traditionally relies on a high level of system understanding, usually expressed in terms of an exact physical model. In contrast to this, reinforcement learning adopts a data-driven approach and constructs an optimal control strategy by interacting with the underlying system. To keep the wear of real-world systems as low as possible, the learning process should be short. In our research, we used the state-of-the-art reinforcement learning method PILCO to design a feedback control strategy for the swing-up of the double pendulum on a cart with remarkably few test iterations at the test bench. PILCO stands for “probabilistic inference for learning control” and requires only few expert knowledge for learning. To achieve the swing-up of a double pendulum on a cart to its upper unstable equilibrium position, we introduce additional state restrictions to PILCO, so that the limited cart distance can be taken into account. Thanks to these measures, we were able to learn the swing up at the real test bench for the first time and in only 27 learning iterations.}},
  author       = {{Hesse, Michael and Timmermann, Julia and Hüllermeier, Eyke and Trächtler, Ansgar}},
  journal      = {{Procedia Manufacturing}},
  pages        = {{15 -- 20}},
  title        = {{{A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart}}},
  volume       = {{24}},
  year         = {{2018}},
}

