TY - CHAP A1 - Hoegen, Anne von A1 - Doncker, Rik W. De A1 - Rütters, René T1 - Teaching Digital Control of Operational Amplifier Processes with a LabVIEW Interface and Embedded Hardware T2 - 2020 23rd International Conference on Electrical Machines and Systems (ICEMS) N2 - Control engineering theory is hard to grasp for undergraduates during the first semesters, as it deals with the dynamical behavior of systems also in combination with control strategies on an abstract level. Therefore, operational amplifier (OpAmp) processes are reasonable and very effective systems to connect mathematical description with actual system’s behavior. In this paper, we present an experiment for a laboratory session in which an embedded system, driven by a LabVIEW human machine interface (HMI) via USB, controls the analog circuits.With this setup we want to show the possibility of firstly, analyzing a first order process and secondly, designing a P-and PI-controller. Thereby, the theory of control engineering is always applied to the empirical results in order to break down the abstract level for the students. Y1 - 2020 U6 - https://doi.org/10.23919/ICEMS50442.2020.9290928 N1 - 23rd International Conference on Electrical Machines and Systems (ICEMS), 24-27 November 2020, Hamamatsu, Japan SP - 1117 EP - 1122 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Nees, Franz A1 - Stengel, Ingo A1 - Meister, Vera G. A1 - Barton, Thomas A1 - Herrmann, Frank A1 - Müller, Christian A1 - Wolf, Martin T1 - Angewandte Forschung in der Wirtschaftsinformatik 2020 : Tagungsband zur 33. AKWI-Jahrestagung am 14.09.2020, ausgerichtet von der Hochschule Karlsruhe - Wirtschaft und Technik / hrsg. von Franz Nees, Ingo Stengel, Vera G. Meister, Thomas Barton, Frank Herrmann, Christian Müller, Martin R. Wolf N2 - Tagungsbeiträge aus den Bereichen KI, Prozessorganisation und Plattformen für Geschäftsprozesse, Sicherheit und Datenschutz sowie Prototypen und Modelle. Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-13840 SN - 978-3-944330-66-2 N1 - 33. AKWI-Jahrestagung am 14.09.2020, ausgerichtet von der Hochschule Karlsruhe - Wirtschaft und Technik PB - mana-Buch CY - Heide ER - TY - CHAP A1 - Hoegen, Anne von A1 - Doncker, Rik W. De A1 - Bragard, Michael A1 - Hoegen, Svenja von T1 - Problem-based learning in automation engineering: performing a remote laboratory aession aerving various educational attainments T2 - 2021 IEEE Global Engineering Education Conference (EDUCON) N2 - During the Covid-19 pandemic, vocational colleges, universities of applied science and technical universities often had to cancel laboratory sessions requiring students’ attendance. These above of all are of decisive importance in order to give learners an understanding of theory through practical work.This paper is a contribution to the implementation of distance learning for laboratory work applicable for several upper secondary educational facilities. Its aim is to provide a paradigm for hybrid teaching to analyze and control a non-linear system depicted by a tank model. For this reason, we redesign a full series of laboratory sessions on the basis of various challenges. Thus, it is suitable to serve different reference levels of the European Qualifications Framework (EQF).We present problem-based learning through online platforms to compensate the lack of a laboratory learning environment. With a task deduced from their future profession, we give students the opportunity to develop own solutions in self-defined time intervals. A requirements specification provides the framework conditions in terms of time and content for students having to deal with the challenges of the project in a self-organized manner with regard to inhomogeneous previous knowledge. If the concept of Complete Action is introduced in classes before, they will automatically apply it while executing the project.The goal is to combine students’ scientific understanding with a procedural knowledge. We suggest a series of remote laboratory sessions that combine a problem formulation from the subject area of Measurement, Control and Automation Technology with a project assignment that is common in industry by providing extracts from a requirements specification. Y1 - 2021 U6 - https://doi.org/10.1109/EDUCON46332.2021.9453925 N1 - 2021 IEEE Global Engineering Education Conference (EDUCON), 21-23 April 2021, Vienna, Austria SP - 1605 EP - 1614 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Hüning, Felix A1 - Stüttgen, Marcel T1 - Work in Progress: Interdisciplinary projects in times of COVID-19 crisis – challenges, risks and chances T2 - 2021 IEEE Global Engineering Education Conference (EDUCON) N2 - Project work and inter disciplinarity are integral parts of today's engineering work. It is therefore important to incorporate these aspects into the curriculum of academic studies of engineering. At the faculty of Electrical Engineering and Information Technology an interdisciplinary project is part of the bachelor program to address these topics. Since the summer term 2020 most courses changed to online mode during the Covid-19 crisis including the interdisciplinary projects. This online mode introduces additional challenges to the execution of the projects, both for the students as well as for the lecture. The challenges, but also the risks and chances of this kind of project courses are subject of this paper, based on five different interdisciplinary projects Y1 - 2021 U6 - https://doi.org/10.1109/EDUCON46332.2021.9454006 N1 - 2021 IEEE Global Engineering Education Conference (EDUCON), 21-23 April 2021, Vienna, Austria SP - 1175 EP - 1179 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Hüning, Felix T1 - Sustainable changes beyond covid-19 for a second semester physics course for electrical engineering students T2 - Blended Learning in Engineering Education: challenging, enlightening – and lasting? N2 - The course Physics for Electrical Engineering is part of the curriculum of the bachelor program Electrical Engineering at University of Applied Science Aachen. Before covid-19 the course was conducted in a rather traditional way with all parts (lecture, exercise and lab) face-to-face. This teaching approach changed fundamentally within a week when the covid-19 limitations forced all courses to distance learning. All parts of the course were transformed to pure distance learning including synchronous and asynchronous parts for the lecture, live online-sessions for the exercises and self-paced labs at home. Using these methods, the course was able to impart the required knowledge and competencies. Taking the teacher’s observations of the student’s learning behaviour and engagement, the formal and informal feedback of the students and the results of the exams into account, the new methods are evaluated with respect to effectiveness, sustainability and suitability for competence transfer. Based on this analysis strong and weak points of the concept and countermeasures to solve the weak points were identified. The analysis further leads to a sustainable teaching approach combining synchronous and asynchronous parts with self-paced learning times that can be used in a very flexible manner for different learning scenarios, pure online, hybrid (mixture of online and presence times) and pure presence teaching. Y1 - 2021 SN - 978-2-87352-023-6 N1 - SEFI 49th Annual Conference, Technische Universität Berlin (online), 13 – 16 September 2021 SP - 1424 EP - 1428 ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Elsen, Ingo A1 - Schiffer, Stefan T1 - Machine learning based 3D object detection for navigation in unstructured environments T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) N2 - In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine. KW - 3D object detection KW - LiDAR KW - autonomous driving KW - Deep learning KW - Three-dimensional displays Y1 - 2021 SN - 978-1-6654-7921-9 U6 - https://doi.org/10.1109/IVWorkshops54471.2021.9669218 N1 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021, Nagoya, Japan. SP - 236 EP - 242 PB - IEEE ER - TY - CHAP A1 - Ritschel, Konstantin A1 - Stenzel, Adina A1 - Czarnecki, Christian A1 - Hong, Chin-Gi ED - Gesellschaft für Informatik e.V. (GI), T1 - Realizing robotic process automation potentials: an architectural perspective on a real-life implementation case T2 - GI Edition Proceedings Band 314 "INFORMATIK 2021" Computer Science & Sustainability N2 - The initial idea of Robotic Process Automation (RPA) is the automation of business processes through a simple emulation of user input and output by software robots. Hence, it can be assumed that no changes of the used software systems and existing Enterprise Architecture (EA) is required. In this short, practical paper we discuss this assumption based on a real-life implementation project. We show that a successful RPA implementation might require architectural work during analysis, implementation, and migration. As practical paper we focus on exemplary lessons-learned and new questions related to RPA and EA. KW - Robotic Process Automation KW - Enterprise Architecture KW - Implementation Case Y1 - 2021 SN - 9783885797081 U6 - https://doi.org/10.18420/informatik2021-108 SN - 1617-5468 N1 - INFORMATIK 2021 – 51. Jahrestagung der Gesellschaft für Informatik, 27. September – 01. Oktober 2021 / Virtuell SP - 1303 EP - 1311 PB - Köllen CY - Bonn ER - TY - CHAP A1 - Müller, Tim M. A1 - Schmitt, Andreas A1 - Leise, Philipp A1 - Meck, Tobias A1 - Altherr, Lena A1 - Pelz, Peter F. A1 - Pfetsch, Marc E. T1 - Validation of an optimized resilient water supply system T2 - Uncertainty in Mechanical Engineering N2 - Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems. KW - Optimization KW - Mixed-integer nonlinear programming KW - Water distribution system KW - Resilience KW - Validation Y1 - 2021 SN - 978-3-030-77255-0 SN - 978-3-030-77256-7 U6 - https://doi.org/10.1007/978-3-030-77256-7_7 N1 - Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), June 7–8, 2021 SP - 70 EP - 80 PB - Springer CY - Cham ER - TY - CHAP A1 - Chajan, Eduard A1 - Schulte-Tigges, Joschua A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Matheis, Dominik A1 - Walter, Thomas T1 - GPU based model-predictive path control for self-driving vehicles T2 - IEEE Intelligent Vehicles Symposium (IV) N2 - One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments. KW - Heuristic algorithms KW - Computational modeling KW - model-predictive control KW - GPU KW - autonomous driving Y1 - 2021 SN - 978-1-7281-5394-0 U6 - https://doi.org/10.1109/IV48863.2021.9575619 N1 - 2021 IEEE Intelligent Vehicles Symposium (IV), July 11-17, 2021. Nagoya, Japan SP - 1243 EP - 1248 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Hüning, Felix A1 - Wache, Franz-Josef A1 - Magiera, David T1 - Redundant bus systems using dual-mode radio T2 - Proceedings of Sixth International Congress on Information and Communication Technology N2 - Communication via serial bus systems, like CAN, plays an important role for all kinds of embedded electronic and mechatronic systems. To cope up with the requirements for functional safety of safety-critical applications, there is a need to enhance the safety features of the communication systems. One measure to achieve a more robust communication is to add redundant data transmission path to the applications. In general, the communication of real-time embedded systems like automotive applications is tethered, and the redundant data transmission lines are also tethered, increasing the size of the wiring harness and the weight of the system. A radio link is preferred as a redundant transmission line as it uses a complementary transmission medium compared to the wired solution and in addition reduces wiring harness size and weight. Standard wireless links like Wi-Fi or Bluetooth cannot meet the requirements for real-time capability with regard to bus communication. Using the new dual-mode radio enables a redundant transmission line meeting all requirements with regard to real-time capability, robustness and transparency for the data bus. In addition, it provides a complementary transmission medium with regard to commonly used tethered links. A CAN bus system is used to demonstrate the redundant data transfer via tethered and wireless CAN. Y1 - 2021 SN - 978-981-16-2379-0 SN - 978-981-16-2380-6 U6 - https://doi.org/10.1007/978-981-16-2380-6_73 N1 - Sixth International Congress on Information and Communication Technology, ICICT 2021, Brunel University, London, February 25–26, 2021 SP - 835 EP - 842 PB - Springer CY - Singapore ER -