Optimal Spacecraft Rendezvous Using Genetic Algorithms

Kim, Young Ha; Spencer, David B.

doi:10.2514/2.3908

Cited by 78 publications

(35 citation statements)

References 1 publication

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“…The GA is a random search method that works by imitating the biological law of evolution from nature, 18 which is ''survival of the fittest, extinction of the unfitness.'' Advantages of the GA include limitless continuity and derivation of function, intrinsic implicit parallelism and better global optimization ability, the search space of automatic acquisition and guide optimization, and adaptive adjusting of the search direction.…”

Section: Hybrid Gamentioning

confidence: 99%

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Zhang

Zhao

Zhang

et al. 2015

Advances in Mechanical Engineering

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In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy-Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation. KeywordsOptimization rendezvous, path constraints, hybrid genetic algorithm, trajectory planning, trajectory tracking On-orbit service, autonomous rendezvous, and docking play the part of key technology in future space activities such as orbital life extension of geosynchronous earth orbit (GEO) satellites, capture of passive satellites, and the space debris removal.1 These technologies require close-proximity operation including the inspection phase and the final approach phase.2 Regarding these space missions, the difficulty of research is compounded by problems related to planning approaches and control with fuel-optimal rendezvous in the closeproximity operation phases.Facing the trajectory design of close-range rendezvous, scholars have made fruitful achievements using primer vector theory proposed by Lawden 3 with the first-order necessary conditions for propellant-optimal trajectories. Prussing and Chiu 4 obtained the optimal, time-fixed, multiple-impulse solutions for both coplanar and a restricted class of noncoplanar circle-to-circle rendezvous. For the fixed-time problem, Carter and colleagues 5,6 present new necessary and sufficiency conditions that do not require global calculation of the

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Section: Hybrid Gamentioning

confidence: 99%

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Zhang

Zhao

Zhang

et al. 2015

Advances in Mechanical Engineering

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“…For example, the PSO algorithm is inspired by the social behavior of a swarm of birds or insects [Crispin (2005)]. Orbital transfer problems and cooperative rendezvous problems using an optimal control formulation have been studied by many authors [Pourtakdous & Jalali (1995); Marinescu (1976); Park & Guibout (2006);Jezewski (1992); Rauwolf & Coverstone-Carroll (1996); Carpenter & Jackson (2003); Kim & Spencer (2002); Olsen & Fowler (2005)]. A Hamiltonian formulation was used as a solution searching method by Marinescu [Marinescu (1976)] and Pourtakdoust [Pourtakdous & Jalali (1995)].…”

Section: Introductionmentioning

confidence: 99%

“…They used the Clohessy-Wiltshire equations as a linear approximation for preliminary mission planning. Another chaser-target type problem is studied by Kim and Spencer [Kim & Spencer (2002)] with minimum fuel consumption as the objective function. Olsen and Fowler [Olsen & Fowler (2005)] also adopted the GA to generate a near optimal solution to a rendezvous problem using elliptic orbits.…”

Section: Introductionmentioning

confidence: 99%

Rendezvous between Two Active Spacecraft with Continuous Low Thrust

Crispin¹,

Seo²

2011

Advances in Spacecraft Technologies

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“…Many different methods have been proposed and tested on a variety of cases. From pure Genetic Algorithms [1][2][3][4] to Evolutionary Strategies (such as Differential Evolution) 5 to hybrid methods, 8 the general intent is to improve over the pure grid or enumerative search. Sometimes, the actual advantage of using a global method is difficult to appreciate, in particular when stochastic based techniques are used.…”

Section: Introductionmentioning

confidence: 99%

On Testing Global Optimization Algorithms for Space Trajectory Design

Vasile

Minisci

Locatelli

2008

AIAA/AAS Astrodynamics Specialist Conference and Exhibit

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In this paper we discuss the procedures to test a global search algorithm applied to a space trajectory design problem. Then, we present some performance indexes that can be used to evaluate the effectiveness of global optimization algorithms. The performance indexes are then compared highlighting the actual significance of each one of them. A number of global optimization algorithms are tested on four typical space trajectory design problems. From the results of the proposed testing procedure we infer for each pair algorithm-problem the relation between the heuristics implemented in the solution algorithm and the main characteristics of the problem under investigation. From this analysis we derive a novel interpretation of some evolutionary heuristics, based on dynamical system theory and we significantly improve the performance of one of the tested algorithms.

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Optimal Spacecraft Rendezvous Using Genetic Algorithms

Cited by 78 publications

References 1 publication

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Rendezvous between Two Active Spacecraft with Continuous Low Thrust

On Testing Global Optimization Algorithms for Space Trajectory Design

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