A guidance approach to satellite formation reconfiguration based on convex optimization and genetic algorithms

Sarno, S.; Guo, Jian; D’Errico, Marco; Gill, Eberhard

doi:10.1016/j.asr.2020.01.033

Cited by 27 publications

(12 citation statements)

References 19 publications

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“…GA is applied in various fields of technologies, applied sciences, and engineering that work through its reproduction operators. In recent years, GA and PSO based heuristic optimization solvers have been applied in transportation planning and logistics management [ 34 ], microgrid energy management systems [ 35 ], optimization of multimodal functions [ 36 ], mobile position estimation problem [ 37 ], the vehicle routing problem in cloud implementation [ 38 ], satellite formation reconfiguration [ 39 ], and the optimization of multi-objective energy models [ 40 ].…”

Section: Methodology: Ann-ga-sqpmmentioning

confidence: 99%

Artificial Neural Networks to Solve the Singular Model with Neumann–Robin, Dirichlet and Neumann Boundary Conditions

Nisar

Sabir

Raja

et al. 2021

Sensors

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The aim of this work is to solve the case study singular model involving the Neumann–Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic programming method (SQPM), i.e., ANN-GA-SQPM. The inspiration to present this numerical framework comes through the objective of introducing a reliable structure that associates the operative ANNs features using the optimization procedures of soft computing to deal with such stimulating systems. Four different problems that are based on the singular equations involving Neumann–Robin, Dirichlet, and Neumann boundary conditions have been occupied to scrutinize the robustness, stability, and proficiency of the designed ANN-GA-SQPM. The proposed results through ANN-GA-SQPM have been compared with the exact results to check the efficiency of the scheme through the statistical performances for taking fifty independent trials. Moreover, the study of the neuron analysis based on three and 15 neurons is also performed to check the authenticity of the proposed ANN-GA-SQPM.

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Section: Methodology: Ann-ga-sqpmmentioning

confidence: 99%

Artificial Neural Networks to Solve the Singular Model with Neumann–Robin, Dirichlet and Neumann Boundary Conditions

Nisar

Sabir

Raja

et al. 2021

Sensors

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“…As described in Section 1, some research has already been proposed to study optimal manoeuvre for formation flying (Sabatini & Palmerini, 2009;Morgan et al, 2014;Sarno et al, 2020). Starting from the work done in literature, we propose and apply an optimal reconfiguration method to close formation flying, with the focus on the most relevant manoeuvre required during mission operations.…”

Section: Problem Definitionmentioning

confidence: 99%

“…He proposed a convex approximation of the prohibited zone for a collision-free flight area of the swarms of spacecraft. A similar approach was described by Sarno et al (2020), who proposed an autonomous low thrust reconfiguration for a distributed system when the relative distances are in the order of hundreds of metres. The path planning was optimised via genetic algorithms and integrated with a convex optimisation law for rapid onboard computation of the control law.…”

Section: Introductionmentioning

confidence: 98%

“…The concept of formation flying reconfiguration has been extensively analysed in the literature (Tillerson et al, 2002;Armellin et al, 2004;Acikmese et al, 2006;Morgan et al, 2014;Koenig & D'Amico, 2018;Sarno et al, 2020). Acikmese et al (2006) proposed a guidance algorithm for formation reconfiguration with heuristic collision avoidance constraints when the satellite distances are in the order of tens of metres.…”

Section: Introductionmentioning

confidence: 99%

“…The development of an inter-satellite collision avoidance strategy is presented, to deal with the close proximity of the satellites. The strategy proposed exploits the benefits of the convex optimisation, to find the global optima of the control law, as in Morgan et al (2014) and Sarno et al (2020). Additional constraints are introduced in the definition of the problem, to simulate a real mission scenario.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Design of optimal low-thrust manoeuvres for remote sensing multi-satellite formation flying in low Earth orbit

Scala,

Gaias,

Colombo

et al. 2022

Preprint

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This paper presents a strategy for optimal manoeuvre design of multi-satellite formation flying in low Earth orbit environment, with the aim of providing a tool for mission operation design. The proposed methodology for formation flying manoeuvres foresees a continuous low-thrust control profile, to enable the operational phases. The design is performed starting from the dynamic representation described in the relative orbital elements, including the main orbital perturbations effects. It also exploits an interface with the classical radial-transversal-normal description to include the maximum delta-v limitation and the safety condition requirements. The methodology is applied to a remote sensing mission study, Formation Flying L-band Aperture Synthesis, for land and ocean application, such as a potential high-resolution Soil Moisture and Ocean Salinity (SMOS) follow-on mission, as part of a European Space Agency mission concept study. Moreover, the results are applicable to a wide range of low Earth orbit missions, exploiting a distributed system, and in particular to Formation Flying L-band Aperture Synthesis (FFLAS) as a follow-on concept to SMOS.

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Time-Varying Lyapunov Control Laws with Enhanced Estimation of Distribution Algorithm for Low-Thrust Trajectory Design

Shirazi

Holt

Armellín

et al. 2023

Springer Optimization and Its Applications

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Enhancements in evolutionary optimization techniques are rapidly growing in many aspects of engineering, specifically in astrodynamics and space trajectory optimization and design. In this chapter, the problem of optimal design of space trajectories is tackled via an enhanced optimization algorithm within the framework of Estimation of Distribution Algorithms (EDAs), incorporated with Lyapunov and Q-law feedback control methods. First, both a simple Lyapunov function and a Q-law are formulated in Classical Orbital Elements (COEs) to provide a closed-loop low-thrust trajectory profile. The weighting coefficients of these controllers are approximated with various degrees of Hermite interpolation splines. Following this model, the unknown time series of weighting coefficients are converted to unknown interpolation points. Considering the interpolation points as the decision variables, a black-box optimization problem is formed with transfer time and fuel mass as the objective functions. An enhanced EDA is proposed and utilized to find the optimal variation of weighting coefficients for minimum-time and minimum-fuel transfer trajectories. The proposed approach is applied in some trajectory optimization problems of Earth-orbiting satellites. Results show the efficiency and the effectiveness of the proposed approach in finding optimal transfer trajectories. A comparison between the Q-law and simple Lyapunov controller is done to show the potential of the potential of the EEDA in enabling the simple Lyapunov controller to recover the finer nuances explicitly given within the analytical expressions in the Q-law.

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A guidance approach to satellite formation reconfiguration based on convex optimization and genetic algorithms

Cited by 27 publications

References 19 publications

Artificial Neural Networks to Solve the Singular Model with Neumann–Robin, Dirichlet and Neumann Boundary Conditions

Artificial Neural Networks to Solve the Singular Model with Neumann–Robin, Dirichlet and Neumann Boundary Conditions

Design of optimal low-thrust manoeuvres for remote sensing multi-satellite formation flying in low Earth orbit

Time-Varying Lyapunov Control Laws with Enhanced Estimation of Distribution Algorithm for Low-Thrust Trajectory Design

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