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Design of End-to-End Trojan Asteroid Rendezvous Tours Incorporating Scientific Value

JOURNAL OF SPACECRAFT AND ROCKETS 2016年第2期53卷 278-288页

作者： Stuart, Jeffrey R. Howell, Kathleen C. Wilson, Roby S. Purdue Univ Sch Aeronaut & Astronaut 701 West Stadium Ave W Lafayette IN 47907 USA Purdue Univ Sch Aeronaut & Astronaut Aeronaut & Astronaut 701 West Stadium Ave W Lafayette IN 47907 USA CALTECH Jet Prop Lab Mission Design & Nav Sect Nav & Mission Design Syst Engn Grp 4800 Oak Grove Dr Pasadena CA 91109 USA CALTECH Jet Prop Lab Mission Design & Nav Sect Inner Planet Mission Anal Grp 4800 Oak Grove Dr Pasadena CA 91109 USA

The sun-Jupiter Trojan asteroids are celestial bodies of great scientific interest as well as potential natural assets offering mineral resources for long-term human exploration of the Solar System. Previous investigations have addressed the automated design of tours within the asteroid swarm and the transition of prospective tours to higher-fidelity, end-to-end trajectories. The current development incorporates the route-finding ant colony optimization algorithm into the automated tour-generation procedure. Furthermore, the potential scientific merit of the destination asteroids is incorporated such that encounters with higher-value asteroids are preferentially incorporated during sequence creation.

关键词： Asteroid Collisions Solar System ant colony optimization algorithms Propellant Astrodynamics Saturn Search Algorithm Sample Return Missions Astronomical Unit Plasma Propulsion System

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optimization for Multitarget, Multispacecraft Impulsive Rendezvous Considering J2 Perturbation

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2021年第10期44卷 1811-1822页

作者： Chen, Shiyu Jiang, Fanghua Li, Haiyang Baoyin, Hexi Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China

optimization for active debris removal using multiple spacecraft is investigated. The main challenge is to determine the rendezvous sequences of the targets considering the J(2) perturbation, which is a large-scale dynamic combinatorial optimization problem. A framework to solve this problem is presented. First, a semi-analytical method of fast estimation for characteristic velocity is proposed to help construct the sequences. The K-medoid method is applied to distribute all the targets to multiple spacecraft so that each spacecraft can remove as many targets as possible with limited propellant. Given a distribution of targets, the sequences for each spacecraft are searched separately;thus the original combinatorial optimization problem is split into multiple small-scale ones that can be efficiently solved by tree search algorithms. An evolutionary algorithm nested with a tree search algorithm is proposed to improve the distribution of the targets, so that the spacecraft can remove all the targets with a low cost. Then optimal sequences are further searched using an ant colony optimization algorithm, and the rendezvous epochs are refined by a nonlinear programming algorithm. The efficiency of these methods is demonstrated by two scenarios of active debris removal.

关键词： Propellant Characteristic Velocity Nonlinear Programming Particle Swarm optimization Search Algorithm ant colony optimization algorithms Trajectory optimization Earth Orbital Elements Orbital Period

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optimization of Active Debris Removal Missions with Multiple Targets

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JOURNAL OF SPACECRAFT AND ROCKETS 2018年第1期55卷 181-189页

作者： Shen, Hong-Xin Zhang, Tian-Jiao Casalino, Lorenzo Pastrone, Dario Xian Satellite Control Ctr State Key Lab Astronaut Dynam Xian 710043 Shaanxi Peoples R China Peking Univ Dept Mech & Engn Sci Beijing 100871 Peoples R China Xi An Jiao Tong Univ Dept Elect & Informat Engn Xian 710049 Shaanxi Peoples R China Polytech Univ Turin Dipartimento Ingn Meccan & Aerospaziale Corso Duca Abruzzi 24 I-10126 Turin Italy

Mission design for multiple debris removal is performed by selecting the most favorable sequences of objects to be removed. Debris items among a population with similar inclination values are considered. The chaser rendezvouses with the objects and attaches a removal kit. An approximate analysis, based on the use of the J2 effect to minimize propellant consumption, provides estimations of transfer times and Delta V between any object pair in order to evaluate the costs of any possible sequence. Estimations, which are verified by using an evolutionary optimization of four-impulse transfers that take J2 perturbation into account, are fast and accurate;and they permit evaluation of all available sequences when the number of objects to be removed is limited. The object sequence determination problem is converted to a traveling salesman problem, and an ant colony optimization algorithm is introduced to analyze longer sequences. The mass of the removal kit for any debris item is then evaluated, depending on the selected removal method. The overall mission mass budget is finally computed, and the best opportunities in terms of the mass and mission time are selected. Different removal techniques exploiting chemical and electric propulsion are compared. The results prove that removal of four to eight objects in less than a year is feasible with current technologies.

关键词： Hybrid Propellants Electric Propulsion ant colony optimization algorithms Earth Periapsis Chemical Propulsion Orbital Elements Hall Thruster Rockets Propulsion System

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Automated Multigravity Assist Trajectory Planning with a Modified ant colony Algorithm

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JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION 2010年第9期7卷 261-293页

作者： Ceriotti, Matteo Vasile, Massimiliano Univ Strathclyde Glasgow Lanark Scotland Univ Glasgow Glasgow Lanark Scotland

The paper presents an approach to transcribe a multigravity assist trajectory design problem into an integrated planning and scheduling problem. A modified ant colony optimization algorithm is then used to generate optimal plans corresponding to optimal sequences of gravity assists and deep space maneuvers to reach a given destination. The modified ant colony Algorithm is based on a hybridization between standard ant colony optimization paradigms and a tabu-based heuristic. The scheduling algorithm is integrated into the trajectory model to provide a fast time-allocation of the events along the trajectory. The approach demonstrated to be very effective on a number of real trajectory design problems.

关键词： Deep Space Maneuver ant colony optimization algorithms Saturn Pericenter ESA Genetic Algorithm Planetary Orbits Gravity Assist Maneuver Orbital Elements Black Box

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optimization-Based Scheduling Method for Agile Earth-Observing Satellite Constellation

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2018年第11期15卷 611-626页

作者： Cho, Doo-Hyun Kim, Jun-Hong Choi, Han-Lim Ahn, Jaemyung Korea Adv Inst Sci & Technol Dept Aerosp Engn Daejeon 34141 South Korea

This Paper proposes a two-step binary linear programming formulation for task scheduling of a constellation of low-Earth-orbit satellites and demonstrates its applicability and scalability to obtain high-quality solutions using a standard mixed-integer linear programming solver. In this instance, the goal of satellite constellation task scheduling is to allocate each task for the satellites and to determine the task starting times in order to maximize the overall mission performance metric. The scheduling problem is formulated to find the solution by first finding a set of candidate communication time intervals for each satellite/ground-station pair as one of the key constraints and time tabling the observation task to acquire the user-requested data, with the incorporation of key constraints for satellite constellation operation. Numerical experiments are designed for investigating the trends, sensitivity, and characteristics of scheduling outputs based on multiple representative instances. The performance of the scheduling solutions by the proposed two-step binary linear programming method exhibits significant improvement of up to 35% in the number of assignments and the sum of profits over the general greedy algorithm.

关键词： Low Earth Orbit Satellites Earth Branch and Bound Algorithm Constellations ant colony optimization algorithms Mixed Integer Linear Programming Satellite Ground Station Ground Station EOS Data Store

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Two-Stage Dynamic-Assignment optimization Method for Multispacecraft Debris Removal

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2022年第9期45卷 1750-1759页

作者： Zhang, Nan Chen, Shiyu Zhang, Zhong Baoyin, Hexi Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China Beijing Inst Spacecraft Syst Engn Beijing 100094 Peoples R China

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Intelligence-Based Multistage optimization Framework for Multiple Debris Removal Mission

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2024年第7期47卷 1447-1456页

作者： Zhu, Yue-He Zhang, Yu Luo, Ya-Zhong Zhang, Jia-Cheng Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Peoples R China

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Global optimization of Multiple-Spacecraft Rendezvous Mission via Decomposition and Dynamics-Guide Evolution Approach

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2022年第1期45卷 171-178页

作者： Huang, An-yi Luo, Ya-zhong Li, Heng-nian Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Peoples R China Xian Satellite Control Ctr Xian 710043 Peoples R China Hunan Key Lab Intelligent Planning & Simulat Aero Changsha 410073 Peoples R China

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Using river formation dynamics to design heuristic algorithms

Using river formation dynamics to design heuristic algorithm...

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6th International Conference on Unconventional Computation

作者： Rabanal, Pablo Rodriguez, Ismael Rubio, Fernando Univ Complutense Madrid Fac Informat Dept Sistemas Informat & Computacin E-28040 Madrid Spain

ISBN: (纸本)9783540735533

Finding the optimal solution to NP-hard problems requires at least exponential time. Thus, heuristic methods are usually applied to obtain acceptable solutions to this kind of problems. In this paper we propose a new type of heuristic algorithms to solve this kind of complex problems. Our algorithm is based on river formation dynamics and provides some advantages over other heuristic methods, like ant colony optimization methods. We present our basic scheme and we illustrate its usefulness applying it to a concrete example: The Traveling Salesman Problem.

关键词： Traveling Salesman Problem nature-based algorithms heuristic algorithms ant colony optimization algorithms

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Modeling and optimization for Hybrid Layout Design with behavioural Constraints

Modeling and Optimization for Hybrid Layout Design with beha...

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IEEE International Conference on Mechatronics and Automation

作者： Zhang, Hong Li, Ai-ping Liu, Xue-mei Tongji Univ Inst Adv Mfg Technol Shanghai 200092 Peoples R China

ISBN: (纸本)9781424426928

As a complex engineering problem, the hybrid layout design with behavioural constraints is difficult to resolve by using conventional approaches. The challenges stem from three aspects: computational complexity, engineering complexity, and engineering practicability. This paper addresses the major issue in establishing three-dimensional layout models to support optimization calculation and constructing the efficient optimization algorithm to get the layout scheme. Based on the octree modeling algorithm, a three-dimensional solid model expression method on layout design is proposed to solve the corresponding problems. The error analysis of the octree expression model is given by comparing with design schemes. The mathematics models of layout problem are established on the design requirements, and then an efficient layout algorithm base on improved ant colony optimization algorithms is given for solving combinatorial optimization problems on layout design. The flow chart of algorithms is given. At last, the design examples are given to illustrate effectiveness with respect to the layout design scheme.

关键词： Hybrid layout optimization Octree modeling algorithm ant colony optimization algorithms Layout design scheme

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