Fuel-Optimal Multi-Impulse Orbit Transfer Using a Hybrid Optimization Method

Hong-yu, Zhou; Wang, Xiaogang; Cui, Naigang

doi:10.1109/tits.2019.2905586

Cited by 7 publications

(4 citation statements)

References 32 publications

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“…ω e represents the angular velocity of the earth's rotation. An orbit in the three-dimensional space can be represented by six orbital elements [16]: For an elliptical orbit, the following formula can be obtained:…”

Section: Formulation Of the Ascent Trajectorymentioning

confidence: 99%

“…This kind of conversion can be realized by many developed methods, for example, the shooting method, the pseudospectral method, the convex method, and heuristic algorithms [10][11][12][13]. Then, the nonlinear planning problem is solved by a group of classical optimization methods, including the sequential quadratic programming, the simulated annealing, particle swarm optimization (PSO) method, and the genetic algorithm [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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Multiconstrained Ascent Trajectory Optimization Using an Improved Particle Swarm Optimization Method

Lin

Zhang

Hong-yu

et al. 2021

International Journal of Aerospace Engineering

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This paper researches the ascent trajectory optimization problem in view of multiple constraints that effect on the launch vehicle. First, a series of common constraints that effect on the ascent trajectory are formulated for the trajectory optimization problem. Then, in order to reduce the computational burden on the optimal solution, the restrictions on the angular momentum and the eccentricity of the target orbit are converted into constraints on the terminal altitude, velocity, and flight path angle. In this way, the requirement on accurate orbit insertion can be easily realized by solving a three-parameter optimization problem. Next, an improved particle swarm optimization algorithm is developed based on the Gaussian perturbation method to generate the optimal trajectory. Finally, the algorithm is verified by numerical simulation.

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Section: Formulation Of the Ascent Trajectorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiconstrained Ascent Trajectory Optimization Using an Improved Particle Swarm Optimization Method

Lin

Zhang

Hong-yu

et al. 2021

International Journal of Aerospace Engineering

Self Cite

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“…Lu et al presented a new methodology for a spacecraft to autonomously rendezvous with a target spacecraft in an arbitrary orbit [2]. The N-impulse rendezvous problem was formalized by Zhou et al and an improved particle swarm optimization method was proposed to solve the problem [3]. The minimum-fuel trajectory design problem was constructed by Zhao et al and solved by the indirect optimization method [4].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Covariance Analysis-Based Robust Rendezvous Trajectory Design by Improved Differential Evolution Method

Jia

Yin

Lei³

et al. 2022

Aerospace

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This paper presents a robust trajectory design method for approaching and rendezvous with a space target considering multi-source uncertainties. A nonlinear covariance analysis method based on the state transition tensor is presented to formulate the propagation of uncertainties including environment parameter uncertainty, actuator error, sensor noise, navigation error and initial state dispersion of the closed-loop GN&C system. Then, the robust trajectory design problem is defined based on the quantified effect of the uncertainties, and an improved self-adaptive differential evolution algorithm is presented to solve the robust trajectory design problem with uncertainties. Finally, four groups of numerical simulations are carried out to show that the designed robust trajectories can satisfy the final state dispersion constraint under multi-source uncertainties.

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“…In another research, Ant Colony Optimization (ACO) is utilized for active debris removal based on multiple spacecraft in [10]. Also, a hybrid heuristic algorithm based on an improved PSO is developed by Zhou et al [11] for dealing with Earth to Moon transfer. In this research, an EA incorporated with an adaptive conjugate gradient scheme is developed for transfer to Earth-Moon halo orbits.…”

mentioning

confidence: 99%

Adaptive Estimation of Distribution Algorithms for Low-Thrust Trajectory Optimization

Shirazi

2023

Journal of Spacecraft and Rockets

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A direct adaptive scheme is presented as an alternative approach for minimum-fuel low-thrust trajectory design in non-coplanar orbit transfers using fitness landscape analysis (FLA). The spacecraft dynamics is modeled with respect to modified equinoctial elements by considering [Formula: see text] orbital perturbations. Taking into account the timings of thrust arcs, the discretization nodes for thrust profile, and the solution of multi-impulse orbit transfer, a constrained continuous optimization problem is formed for low-thrust orbital maneuvers. An adaptive method within the framework of the estimation of distribution algorithms (EDA) is proposed, which aims at conserving the feasibility of the solutions within the search process. Several problem identifiers for low-thrust trajectory optimization are introduced, and the complexity of the solution domain is analyzed by evaluating the landscape feature of the search space via FLA. Two adaptive operators are proposed, which control the search process based on the need for exploration and exploitation of the search domain to achieve optimal transfers. The adaptive operators are implemented in the presented EDA and several perturbed and nonperturbed orbit transfer problems are solved. The results confirm the effectiveness and reliability of the proposed approach in finding optimal low-thrust transfer trajectories.

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Fuel-Optimal Multi-Impulse Orbit Transfer Using a Hybrid Optimization Method

Cited by 7 publications

References 32 publications

Multiconstrained Ascent Trajectory Optimization Using an Improved Particle Swarm Optimization Method

Multiconstrained Ascent Trajectory Optimization Using an Improved Particle Swarm Optimization Method

Nonlinear Covariance Analysis-Based Robust Rendezvous Trajectory Design by Improved Differential Evolution Method

Adaptive Estimation of Distribution Algorithms for Low-Thrust Trajectory Optimization

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