TY - CHAP A1 - Dachwald, Bernd T1 - Low-Thrust Mission Analysis and Global Trajectory Optimization Using Evolutionary Neurocontrol: New Results T2 - European Workshop on Space Mission Analysis ESA/ESOC, Darmstadt, Germany 10 { 12 Dec 2007 N2 - Interplanetary trajectories for low-thrust spacecraft are often characterized by multiple revolutions around the sun. Unfortunately, the convergence of traditional trajectory optimizers that are based on numerical optimal control methods depends strongly on an adequate initial guess for the control function (if a direct method is used) or for the starting values of the adjoint vector (if an indirect method is used). Especially when many revolutions around the sun are re- quired, trajectory optimization becomes a very difficult and time-consuming task that involves a lot of experience and expert knowledge in astrodynamics and optimal control theory, because an adequate initial guess is extremely hard to find. Evolutionary neurocontrol (ENC) was proposed as a smart method for low-thrust trajectory optimization that fuses artificial neural networks and evolutionary algorithms to so-called evolutionary neurocontrollers (ENCs) [1]. Inspired by natural archetypes, ENC attacks the trajectoryoptimization problem from the perspective of artificial intelligence and machine learning, a perspective that is quite different from that of optimal control theory. Within the context of ENC, a trajectory is regarded as the result of a spacecraft steering strategy that maps permanently the actual spacecraft state and the actual target state onto the actual spacecraft control vector. This way, the problem of searching the optimal spacecraft trajectory is equivalent to the problem of searching (or "learning") the optimal spacecraft steering strategy. An artificial neural network is used to implement such a spacecraft steering strategy. It can be regarded as a parameterized function (the network function) that is defined by the internal network parameters. Therefore, each distinct set of network parameters defines a different network function and thus a different steering strategy. The problem of searching the optimal steering strategy is now equivalent to the problem of searching the optimal set of network parameters. Evolutionary algorithms that work on a population of (artificial) chromosomes are used to find the optimal network parameters, because the parameters can be easily mapped onto a chromosome. The trajectory optimization problem is solved when the optimal chromosome is found. A comparison of solar sail trajectories that have been published by others [2, 3, 4, 5] with ENC-trajectories has shown that ENCs can be successfully applied for near-globally optimal spacecraft control [1, 6] and that they are able to find trajectories that are closer to the (unknown) global optimum, because they explore the trajectory search space more exhaustively than a human expert can do. The obtained trajectories are fairly accurate with respect to the terminal constraint. If a more accurate trajectory is required, the ENC-solution can be used as an initial guess for a local trajectory optimization method. Using ENC, low-thrust trajectories can be optimized without an initial guess and without expert attendance. Here, new results for nuclear electric spacecraft and for solar sail spacecraft are presented and it will be shown that ENCs find very good trajectories even for very difficult problems. Trajectory optimization results are presented for 1. NASA's Solar Polar Imager Mission, a mission to attain a highly inclined close solar orbit with a solar sail [7] 2. a mission to de ect asteroid Apophis with a solar sail from a retrograde orbit with a very-high velocity impact [8, 9] 3. JPL's \2nd Global Trajectory Optimization Competition", a grand tour to visit four asteroids from different classes with a NEP spacecraft Y1 - 2007 ER - TY - CHAP A1 - Loeb, Horst W. A1 - Schartner, Karl-Heinz A1 - Seboldt, Wolfgang A1 - Dachwald, Bernd A1 - Streppel, Joern A1 - Meusemann, Hans A1 - Schülke, Peter T1 - SEP for a lander mission to the jovian moon europa T2 - 57th International Astronautical Congress N2 - Under DLR-contract, Giessen University and DLR Cologne are studying solar-electric propulsion missions (SEP) to the outer regions of the solar system. The most challenging reference mission concerns the transport of a 1.35-tons chemical lander spacecraft into an 80-RJ circular orbit around Jupiter, which would enable to place a 375 kg lander with 50 kg of scientific instruments on the surface of the icy moon "Europa". Thorough analyses show that the best solution in terms of SEP launch mass times thrusting time would be a two-stage EP module and a triple-junction solar array with concentrators which would be deployed step by step. Mission performance optimizations suggest to propel the spacecraft in the first EP stage by 6 gridded ion thrusters, running at 4.0 kV of beam voltage, which would save launch mass, and in the second stage by 4 thrusters with 1.25 to 1.5 kV of positive high voltage saving thrusting time. In this way, the launch mass of the spacecraft would be kept within 5.3 tons. Without a launcher's C3 and interplanetary gravity assists, Jupiter might be reached within about 4 yrs. The spiraling-down into the parking orbit would need another 1.8 yrs. This "large mission" can be scaled down to a smaller one, e.g., by halving all masses, the solar array power, and the number of thrusters. Due to their reliability, long lifetime and easy control, RIT-22 engines have been chosen for mission analysis. Based on precise tests, the thruster performance has been modeled. Y1 - 2006 U6 - https://doi.org/10.2514/6.IAC-06-C4.4.04 N1 - 57th International Astronautical Congress, 02 October 2006 - 06 October 2006, Valencia, Spain. SP - 1 EP - 12 ER - TY - CHAP A1 - Valero, Daniel A1 - Vogel, Jochen A1 - Schmidt, Daniel A1 - Bung, Daniel Bernhard T1 - Three-dimensional flow structure inside the cavity of a non-aerated stepped chute T2 - 7th IAHR International Symposium on Hydraulic Structures, Aachen, Germany, 15-18 May Y1 - 2018 SN - 978-0-692-13277-7 U6 - https://doi.org/10.15142/T3GH17 ER - TY - CHAP A1 - Anthrakidis, Anette A1 - Rusack, Markus A1 - Schwarzer, Klemens T1 - Low effort measurement method of PTC-efficiency T2 - SolarPACES 2010 : the CSP conference: electricity, fuels and clean water from concentrated solar energy ; 21 to 24 September 2010, Perpignan, France Y1 - 2010 SP - 48 EP - 49 PB - Soc. OSC CY - Saint Maur ER - TY - CHAP A1 - Dey, Thomas A1 - Elsen, Ingo A1 - Ferrein, Alexander A1 - Frauenrath, Tobias A1 - Reke, Michael A1 - Schiffer, Stefan ED - Makedon, Fillia T1 - CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom T2 - PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference N2 - In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway. KW - embedded hardware KW - sensor networks KW - information systems KW - education KW - do-it-yourself Y1 - 2021 SN - 9781450387927 U6 - https://doi.org/10.1145/3453892.3462697 N1 - PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June 2021- 2 July 2021 SP - 292 EP - 299 PB - Association for Computing Machinery CY - New York ER - TY - CHAP A1 - Gehler, M. A1 - Ober-Blöbaum, S. A1 - Dachwald, Bernd T1 - Application of discrete mechanics and optimal control to spacecraft in non-keplerian motion around small solar system bodies T2 - Procceedings of the 60th International Astronautical Congress N2 - Prolonged operations close to small solar system bodies require a sophisticated control logic to minimize propellant mass and maximize operational efficiency. A control logic based on Discrete Mechanics and Optimal Control (DMOC) is proposed and applied to both conventionally propelled and solar sail spacecraft operating at an arbitrarily shaped asteroid in the class of Itokawa. As an example, stand-off inertial hovering is considered, recently identified as a challenging part of the Marco Polo mission. The approach is easily extended to stand-off orbits. We show that DMOC is applicable to spacecraft control at small objects, in particular with regard to the fact that the changes in gravity are exploited by the algorithm to optimally control the spacecraft position. Furthermore, we provide some remarks on promising developments. KW - Spacecraft Y1 - 2009 SN - 978-161567908-9 N1 - 60th International Astronautical Congress 2009, IAC 2009; Daejeon; South Korea; 12 October 2009 through 16 October 2009 SP - 1360 EP - 1371 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Kallweit, Stephan A1 - Schleupen, Josef A1 - Dahmann, Peter A1 - Bagheri, Mohsen A1 - Engemann, Heiko T1 - Entwicklung eines Kletterroboters zur Diagnose und Instandsetzung von Windenergieanlagen (SMART) T2 - Automatisierung im Fokus von Industrie 4.0 : Tagungsband AALE 2016 ; 13. Fachkonferenz, Lübeck Y1 - 2016 SN - 978-3-8356-7312-0 N1 - AALE-Konferenz <13., 2016, Lübeck> SP - 207 EP - 212 PB - DIV Deutscher Industrieverlag GmbH CY - München 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 - Dachwald, Bernd T1 - Radiation pressure force model for an ideal laser-enhanced solar sail T2 - 4th International Symposium on Solar Sailing N2 - The concept of a laser-enhanced solar sail is introduced and the radiation pressure force model for an ideal laser-enhanced solar sail is derived. A laser-enhanced solar sail is a “traditional” solar sail that is, however, not solely propelled by solar radiation, but additionally by a laser beam that illuminates the sail. The additional laser radiation pressure increases the sail's propulsive force and can give, depending on the location of the laser source, more control authority over the direction of the solar sail’s propulsive force vector. This way, laser-enhanced solar sails may augment already existing solar sail mission concepts and make novel mission concepts feasible. Y1 - 2017 N1 - 4th International Symposium on Solar Sailing 17-20 January 2017, Kyōto, Japan SP - 1 EP - 5 ER - TY - CHAP A1 - Pham, Phu Tinh A1 - Staat, Manfred T1 - A simplification for shakedown analysis of hardening structures T2 - Conference proceedings of the YIC GACM 2015 : 3rd ECCOMAS Young Investigators Conference and 6th GACM Colloquium on Computational Mechanics , Aachen , Germany, 20.07.2015 - 23.07.2015 / ed.: Stefanie Elgeti ; Jaan-Willem Simon Y1 - 2015 SP - 1 EP - 4 PB - RWTH Aachen University CY - Aachen ER -