TY - JOUR A1 - Dachwald, Bernd T1 - Optimal Solar Sail Trajectories for Missions to the Outer Solar System JF - Journal of guidance, control, and dynamics. 28 (2005), H. 6 Y1 - 2005 SN - 0162-3192 N1 - 2. ISSN: 0162-3192. - 3. ISSN: 0731-5090 SP - 1187 EP - 1193 ER - TY - JOUR A1 - Dachwald, Bernd T1 - Optimization of Interplanetary Solar Sailcraft Trajectories Using Evolutionary Neurocontrol JF - Journal of guidance, control, and dynamics. 27 (2004), H. 1 Y1 - 2004 SN - 0162-3192 N1 - 2. ISSN: 0162-3192. - 3. ISSN: 0731-5090 SP - 66 EP - 72 ER - TY - JOUR A1 - Dachwald, Bernd T1 - Interplanetary Mission Analysis for Non-Perfectly Reflecting Solar Sailcraft Using Evolutionary Neurocontrol JF - Astrodynamics 2003 : proceedings of the AAS/AIAA Astrodynamics Conference held August 3 - 7, 2003, Big Sky, Montana / ed. by Jean de Lafontaine. - Pt. 2. - (Advances in the astronautical sciences ; 116,2) Y1 - 2004 SN - 0-87703-509-1 N1 - Astrodynamics Conference <2003, Big Sky, Mont.> ; American Institute of Aeronautics and Astronautics ; AAS-03-579 SP - 1247 EP - 1262 PB - Univelt CY - San Diego, Calif. ER - TY - JOUR A1 - Dachwald, Bernd T1 - Verwendung eines neuronalen Reglers und evolutionärer Algorithmen zur Berechnung optimaler interplanetarer Sonnenseglerbahnen JF - Deutscher Luft- und Raumfahrtkongress 2003 : München, 17. bis 20. November 2003, Motto: 100 Jahre Motorflug - 112 Jahre Menschenflug: Visionen gestalten Zukunft / Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. (DGLR). [Red.: Peter Brandt (verantwortlich)]. - Bd. 1. - (Jahrbuch ... der Deutschen Gesellschaft für Luft- und Raumfahrt) Y1 - 2003 N1 - Deutscher Luft- und Raumfahrt-Kongreß <2003, München> ; Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth ; DGLR-2002-089 SP - 211 EP - 218 CY - Bonn ER - TY - JOUR A1 - Dachwald, Bernd T1 - Low-Thrust Trajectory Optimization and Interplanetary Mission Analysis Using Evolutionary Neurocontrol JF - Deutscher Luft- und Raumfahrtkongress 2004 : Dresden, 20. bis 23. September 2004, Motto: Luft- und Raumfahrt - Brücke für eine wissensbasierte Gesellschaft / Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. (DGLR). [Red.: Peter Brandt (verantwortlich)]. - Bd. 2. - (Jahrbuch ... der Deutschen Gesellschaft für Luft- und Raumfahrt) Y1 - 2004 N1 - Deutscher Luft- und Raumfahrt-Kongress <2004, Dresden> ; Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth ; DGLR-2004-116 SP - 917 EP - 926 CY - Bonn ER - TY - JOUR A1 - Dachwald, Bernd T1 - Evolutionary Neurocontrol: A Smart Method for Global Optimization of Low-Thrust Trajectories JF - 22nd AIAA Applied Aerodynamics Conference and Exhibit - AIAA/AAS Astrodynamics Specialist Conference and Exhibit - AIAA Guidance, Navigation, and Control Conference and Exhibit - AIAA Modeling and Simulation Technologies Conference and Exhibit - AIAA Atmospheric Flight Mechanics Conference and Exhibit : 16 - 19 August 2004, Providence, Rhode Island / American Institute of Aeronautics and Astronautics. - (AIAA meeting papers on disc ; 2004,14-15) Y1 - 2004 N1 - American Institute of Aeronautics and Astronautics ; AIAA/AAS Astrodynamics Specialist Conference and Exhibit <2004, Providence, RI> ; AIAA paper number: AIAA-2004-5405 PB - American Inst. of Aeronautics and Astronautics CY - Reston, Va. ER - TY - JOUR A1 - Dachwald, Bernd T1 - Optimal Solar Sail Trajectories for Missions to the Outer Solar System JF - 22nd AIAA Applied Aerodynamics Conference and Exhibit - AIAA/AAS Astrodynamics Specialist Conference and Exhibit - AIAA Guidance, Navigation, and Control Conference and Exhibit - AIAA Modeling and Simulation Technologies Conference and Exhibit - AIAA Atmospheric Flight Mechanics Conference and Exhibit : 16 - 19 August 2004, Providence, Rhode Island / American Institute of Aeronautics and Astronautics. - (AIAA meeting papers on disc ; 2004,14-15) Y1 - 2004 N1 - American Institute of Aeronautics and Astronautics ; AIAA/AAS Astrodynamics Specialist Conference and Exhibit <2004, Providence, RI> ; AIAA paper number: AIAA-2004-5406 PB - American Inst. of Aeronautics and Astronautics CY - Reston, Va. ER - 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 - Dachwald, Bernd T1 - Global optimization of low-thrust space missions using evolutionary neurocontrol T2 - Proceedings of the international workshop on global optimization N2 - Low-thrust space propulsion systems enable flexible high-energy deep space missions, but the design and optimization of the interplanetary transfer trajectory is usually difficult. It involves much experience and expert knowledge because the convergence behavior of traditional local trajectory optimization methods depends strongly on an adequate initial guess. Within this extended abstract, evolutionary neurocontrol, a method that fuses artificial neural networks and evolutionary algorithms, is proposed as a smart global method for low-thrust trajectory optimization. It does not require an initial guess. The implementation of evolutionary neurocontrol is detailed and its performance is shown for an exemplary mission. KW - Evolutionary Neurocontrol KW - Spacecraft Trajectory Optimization KW - Low-Thrust Propulsion Y1 - 2005 SP - 85 EP - 90 ER - TY - CHAP A1 - Dachwald, Bernd ED - Knopf, George K. ED - Otani, Yukitoshi T1 - Light propulsion systems for spacecraft T2 - Optical nano and micro actuator technology Y1 - 2017 SN - 9781315217628 (eBook) SP - 577 EP - 598 PB - CRC Press CY - Boca Raton ER -