Omslagsbillede

Distributed Impulsive Multi-Spacecraft Approach Trajectory Optimization Based on Cooperative Game Negotiation

Guardado en:
Udgivet i:Aerospace vol. 12, no. 7 (2025), p. 628-649
Hovedforfatter: Fan Shuhui
Andre forfattere: Zhang, Xiang, Liao Wenhe
Udgivet:
MDPI AG
Fag:
Game theory
Negotiations
Strategy
Games
Optimization techniques
Orbits
Equilibrium
Multiple objective analysis
Spacecraft
Decision making
Energy consumption
Efficiency
Optimization models
Trajectory optimization
Planning
Monte Carlo simulation
Pareto optimization
Engineering
Methods
Simulated annealing
Constraints
Optimization algorithms
Trajectory planning
Entrapment
Orbital mechanics
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Resumen:A cooperative game negotiation strategy considering multiple constraints is proposed for distributed impulsive multi-spacecraft approach missions in the presence of defending spacecraft. It is a dual-stage decision-making method that includes offline trajectory planning and online distributed negotiation. In the trajectory planning stage, a relative orbital dynamics model is first established based on the Clohessy–Wiltshire (CW) equations, and the state transition equations for impulsive maneuvers are derived. Subsequently, a multi-objective optimization model is formulated based on the NSGA-II algorithm, utilizing a constraint dominance principle (CDP) to address various constraints and generate Pareto front solutions for each spacecraft. In the distributed negotiation stage, the negotiation strategy among spacecraft is modeled as a cooperative game. A potential function is constructed to further analyze the existence and global convergence of Nash equilibrium. Additionally, a simulated annealing negotiation strategy is developed to iteratively select the optimal comprehensive approach strategy from the Pareto fronts. Simulation results demonstrate that the proposed method effectively optimizes approach trajectories for multi-spacecraft under complex constraints. By leveraging inter-satellite iterative negotiation, the method converges to a Nash equilibrium. Additionally, the simulated annealing negotiation strategy enhances global search performance, avoiding entrapment in local optima. Finally, the effectiveness and robustness of the dual-stage decision-making method were further demonstrated through Monte Carlo simulations.
ISSN:2226-4310
DOI:10.3390/aerospace12070628
Fuente:Advanced Technologies & Aerospace Database