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Record W2325262716 · doi:10.2514/6.2014-4364

Rigid Spacecraft Formations Actuated by Electric Thrusters with One-Bit Resolution

2014· article· en· W2325262716 on OpenAlexaff
Edoardo Serpelloni, Manfredi Maggiore, Chris J. Damaren

Bibliographic record

VenueAIAA/AAS Astrodynamics Specialist Conference · 2014
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSpacecraftActuatorThrustControl theory (sociology)PropulsionElectrically powered spacecraft propulsionAttitude controlComputer scienceOrientation (vector space)Aerospace engineeringMechanism (biology)Resolution (logic)PhysicsEngineeringControl (management)MathematicsGeometryArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper we investigate a formation control problem for two space vehicles in general multibody regimes. The objective is to accurately regulate the distance between the vehicles, as well as the orientation of the overall formation to a desired, rigid configuration, under tight tolerances. The propulsion mechanism of each spacecraft is given by a collection of low thrust electric thrusters. We show that the formation control problem is solvable using constant thrust electric actuators requiring only one bit of resolution, overcoming the problem of actuator resolution. The control law we propose is hybrid, and it coordinates the sequence of on-off switches of the thrusters so as to achieve the control objective and, at the same time, avoid sliding modes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.171
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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