@inproceedings{WittigRuettersBragard2024,
  author    = {Wittig, M. and R{\"u}tters, Ren{\´e} and Bragard, Michael},
  title     = {Application of RL in control systems using the example of a rotatory inverted pendulum},
  series = {Tagungsband AALE 2024 : Fit f{\"u}r die Zukunft: praktische L{\"o}sungen f{\"u}r die industrielle Automation},
  booktitle = {Tagungsband AALE 2024 : Fit f{\"u}r die Zukunft: praktische L{\"o}sungen f{\"u}r die industrielle Automation},
  editor    = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Schwarz, Andr{\´e}},
  publisher = {le-tex publishing services GmbH},
  address   = {Leipzig},
  isbn      = {978-3-910103-02-3},
  doi       = {10.33968/2024.53},
  pages     = {241 -- 248},
  year      = {2024},
  abstract  = {In this paper, the use of reinforcement learning (RL) in control systems is investigated using a rotatory inverted pendulum as an example. The control behavior of an RL controller is compared to that of traditional LQR and MPC controllers. This is done by evaluating their behavior under optimal conditions, their disturbance behavior, their robustness and their development process. All the investigated controllers are developed using MATLAB and the Simulink simulation environment and later deployed to a real pendulum model powered by a Raspberry Pi. The RL algorithm used is Proximal Policy Optimization (PPO). The LQR controller exhibits an easy development process, an average to good control behavior and average to good robustness. A linear MPC controller could show excellent results under optimal operating conditions. However, when subjected to disturbances or deviations from the equilibrium point, it showed poor performance and sometimes instable behavior. Employing a nonlinear MPC Controller in real time was not possible due to the high computational effort involved. The RL controller exhibits by far the most versatile and robust control behavior. When operated in the simulation environment, it achieved a high control accuracy. When employed in the real system, however, it only shows average accuracy and a significantly greater performance loss compared to the simulation than the traditional controllers. With MATLAB, it is not yet possible to directly post-train the RL controller on the Raspberry Pi, which is an obstacle to the practical application of RL in a prototyping or teaching setting. Nevertheless, RL in general proves to be a flexible and powerful control method, which is well suited for complex or nonlinear systems where traditional controllers struggle.},
  language  = {en}
}
@inproceedings{AltherrDoeringFrauenrathetal.2024,
  author    = {Altherr, Lena and D{\"o}ring, Bernd and Frauenrath, Tobias and Groß, Rolf and Mohan, Nijanthan and Oyen, Marc and Schnittcher, Lukas and Voß, Norbert},
  title     = {DiggiTwin: ein interdisziplin{\"a}res Projekt zur Nutzung digitaler Zwillinge auf dem Weg zu einem klimaneutralen Geb{\"a}udebestand},
  series = {Tagungsband AALE 2024 : Fit f{\"u}r die Zukunft: praktische L{\"o}sungen f{\"u}r die industrielle Automation},
  booktitle = {Tagungsband AALE 2024 : Fit f{\"u}r die Zukunft: praktische L{\"o}sungen f{\"u}r die industrielle Automation},
  editor    = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Schwarz, Andr{\´e}},
  publisher = {le-tex publishing services GmbH},
  address   = {Leipzig},
  isbn      = {978-3-910103-02-3},
  doi       = {10.33968/2024.67},
  pages     = {341 -- 346},
  year      = {2024},
  abstract  = {Im Hinblick auf die Klimaziele der Bundesrepublik Deutschland konzentriert sich das Projekt Diggi Twin auf die nachhaltige Geb{\"a}udeoptimierung. Grundlage f{\"u}r eine ganzheitliche Geb{\"a}ude{\"u}berwachung und -optimierung bildet dabei die Digitalisierung und Automation im Sinne eines Smart Buildings. Das interdisziplin{\"a}re Projekt der FH Aachen hat das Ziel, ein bestehendes Hochschulgeb{\"a}ude und einen Neubau an klimaneutrale Standards anzupassen. Im Rahmen des Projekts werden bekannte Verfahren, wie das Building Information Modeling (BIM), so erweitert, dass ein digitaler Geb{\"a}udezwilling entsteht. Dieser kann zur Optimierung des Geb{\"a}udebetriebs herangezogen werden, sowie als Basis f{\"u}r eine Erweiterung des Bewertungssystems Nachhaltiges Bauen (BNB) dienen. Mithilfe von Sensortechnologie und k{\"u}nstlicher Intelligenz kann so ein pr{\"a}zises Monitoring wichtiger Geb{\"a}udedaten erfolgen, um ungenutzte Energieeinsparpotenziale zu erkennen und zu nutzen. Das Projekt erforscht und setzt methodische Erkenntnisse zu BIM und digitalen Geb{\"a}udezwillingen praxisnah um, indem es spezifische Fragen zur Energie- und Ressourceneffizienz von Geb{\"a}uden untersucht und konkrete L{\"o}sungen f{\"u}r die Geb{\"a}udeoptimierung entwickelt.},
  language  = {de}
}
@inproceedings{KramerBragardRitzetal.2024,
  author    = {Kramer, Pia and Bragard, Michael and Ritz, Thomas and Ferfer, Ute and Schiffers, Tim},
  title     = {Visualizing, Enhancing and Predicting Students' Success through ECTS Monitoring},
  series = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  booktitle = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {2165-9559},
  doi       = {10.1109/EDUCON60312.2024.10578652},
  pages     = {5 Seiten},
  year      = {2024},
  abstract  = {This paper serves as an introduction to the ECTS monitoring system and its potential applications in higher education. It also emphasizes the potential for ECTS monitoring to become a proactive system, supporting students by predicting academic success and identifying groups of potential dropouts for tailored support services. The use of the nearest neighbor analysis is suggested for improving data analysis and prediction accuracy.},
  language  = {en}
}
@inproceedings{RuettersBragardDolls2024,
  author    = {R{\"u}tters, Ren{\´e} and Bragard, Michael and Dolls, Sarah},
  title     = {The Inverted Rotary Pendulum: Facilitating Practical Teaching in Advanced Control Engineering},
  series = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  booktitle = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {2165-9559},
  doi       = {10.1109/EDUCON60312.2024.10578937},
  pages     = {5 Seiten},
  year      = {2024},
  abstract  = {This paper outlines a practical approach to teach control engineering principles, with an inverted rotary pendulum, serving as an illustrative example. It shows how the pendulum is embedded in an advanced course of control engineering. This approach is incorporated into a flipped-classroom concept, as well as classical teaching concepts, offering students practical experience in control engineering. In addition, the design of the pendulum is shown, using a Raspberry Pi as the target platform for Matlab Simulink. This pendulum can be used in the classroom to evaluate the controller design mentioned above. It is analysed if the use of the pendulum generates a deeper understanding of the learning contents.},
  language  = {en}
}
@inproceedings{BeckerBragard2024,
  author    = {Becker, Tim and Bragard, Michael},
  title     = {Low-Voltage DC Training Lab for Electric Drives - Optimizing the Balancing Act Between High Student Throughput and Individual Learning Speed},
  series = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  booktitle = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {2165-9559},
  doi       = {10.1109/EDUCON60312.2024.10578902},
  pages     = {8 Seiten},
  year      = {2024},
  abstract  = {After a brief introduction of conventional laboratory structures, this work focuses on an innovative and universal approach for a setup of a training laboratory for electric machines and drive systems. The novel approach employs a central 48 V DC bus, which forms the backbone of the structure. Several sets of DC machine, asynchronous machine and synchronous machine are connected to this bus. The advantages of the novel system structure are manifold, both from a didactic and a technical point of view: Student groups can work on their own performance level in a highly parallelized and at the same time individualized way. Additional training setups (similar or different) can easily be added. Only the total power dissipation has to be provided, i.e. the DC bus balances the power flow between the student groups. Comparative results of course evaluations of several cohorts of students are shown.},
  language  = {en}
}