Optimization of transfer orbit for multiple-pulse noncoplanar rendezvous and docking

Yuan, 刘源 Liu; Xiao, 叶潇 Ye; Yong, 郝勇 Hao; Yu-ling, 李玉玲 Li

doi:10.3788/ope.20172504.0987

Cited by 2 publications

(3 citation statements)

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“…Initialize all particles' position with random positions in the M-dimensional feasible space of design variables; Step 2. Calculation of particle's fitness: Calculate the value of objective function of each particle from equation (13) or (14); Step 3. Update of pbest (personal best): Compare each particle's fitness with the particle's pbest.…”

Section: Combined Algorithm Of Qpso and Sqpmentioning

confidence: 99%

“…Advanced optimization models of multiple-impulse orbit transfer have been formulated. 13 Population-based evolutionary algorithms such as genetic algorithm (GA) 13 and particle swarm optimization (PSO) 14,15 have been adopted to solve the optimization problems of multiple-impulse orbit transfer. Based on these researches, Li et al 16 finished optimization work of perturbed cooperative rendezvous under impulse thrust with a hybrid optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Optimization results of cooperative rendezvous (equation(14)with ¼ 1). Optimization results of cooperative rendezvous (equation(14) with ¼ 0).…”

mentioning

confidence: 99%

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Optimization for far-distance and fuel-limited cooperative rendezvous between two coplanar spacecraft based on Lambert method

Wang

Dong

Feng

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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Concentrating on far-distance and fuel cooperative rendezvous between two coplanar spacecraft under impulse thrust, this paper presents fuel-optimal results obtained by optimization algorithms numerically. Former research works have formulated optimization models of multiple-impulse orbit transfer and cooperative rendezvous under continuous thrust. In this paper, optimization models of cooperative rendezvous under impulse thrust are formulated based on these former researches. The process of cooperative rendezvous is simplified by introducing a hypothetical spacecraft. The degradation from cooperative rendezvous to active–passive rendezvous is prevented by revising objective functions. Quantum-behaved particle swarm optimization and sequential quadratic programming are combined to solve a practical problem, which is used to illustrate advantages of cooperative rendezvous when fuel consumption of one spacecraft is limited.

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Section: Combined Algorithm Of Qpso and Sqpmentioning

confidence: 99%