The paper proposes an approach to search the suitable solution of the differential drag control using the Particle Swarm Optimization (PSO). This method presumes the evolution of a group of candidate solutions called particles that move through the feasible search space, which indicates the set of all acceptable and meaningful solutions. The PSO integrates the dynamics and evaluates the particles w.r.t. the fitness function, the trajectory constraints, the final conditions and the control bounds. During the evolution, each particle is evaluated according to a numerical value and determined through a fitness function. Recently, the authors of this paper have proposed a modified technique, named Inverse Dynamics Particle Swarm Optimization (iPSO), which does not involve the integration of the dynamics and where the trajectory constraints and the final conditions are directly satisfied. The paper shows the preliminary results of the iPSO applied to the problem of rendezvous of a pair of nanosatellites, when the differential drag control is used, and the fitness function includes the time of the maneuver, the difference between the two final orbital positions and the difference between the two final orbital velocities.
Inverse dynamics particle swarm optimization for nanosatellites rendezvous via differential drag / Spiller, Dario; Curti, Fabio. - STAMPA. - 2:4(2016), pp. 255-280. (Intervento presentato al convegno 3rd IAA Conference on University Satellite Missions and CubeSat Workshop & International Workshop on Lean Satellite Standardization tenutosi a Rome, Italy nel 30 Novembre - 5 Dicembre).
Inverse dynamics particle swarm optimization for nanosatellites rendezvous via differential drag
SPILLER, DARIO
Conceptualization
;CURTI, FabioMethodology
2016
Abstract
The paper proposes an approach to search the suitable solution of the differential drag control using the Particle Swarm Optimization (PSO). This method presumes the evolution of a group of candidate solutions called particles that move through the feasible search space, which indicates the set of all acceptable and meaningful solutions. The PSO integrates the dynamics and evaluates the particles w.r.t. the fitness function, the trajectory constraints, the final conditions and the control bounds. During the evolution, each particle is evaluated according to a numerical value and determined through a fitness function. Recently, the authors of this paper have proposed a modified technique, named Inverse Dynamics Particle Swarm Optimization (iPSO), which does not involve the integration of the dynamics and where the trajectory constraints and the final conditions are directly satisfied. The paper shows the preliminary results of the iPSO applied to the problem of rendezvous of a pair of nanosatellites, when the differential drag control is used, and the fitness function includes the time of the maneuver, the difference between the two final orbital positions and the difference between the two final orbital velocities.File | Dimensione | Formato | |
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