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Record W2335751212 · doi:10.2514/6.2013-5240

Optimal Hybrid Control for Lorentz-Augmented Formation Flying

2013· article· en· W2335751212 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIAA Guidance, Navigation, and Control (GNC) Conference · 2013
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl (management)Control theory (sociology)Computer scienceOptimal controlMathematical optimizationArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

The problem of optimal control for a linear time-varying system with both continuous and impulsive control inputs is considered. The solution to the hybrid linear quadratic regular (LQR) problem, obtained using the Minimum Principle, is presented, with an emphasis on the solution to the corresponding discontinuous Riccati equation. The hybrid LQR is applied to the problem of Lorentz-augmented formation maintenance, where the deputy spacecraft mitigates the effects of the J2 perturbation using a combination of the geomagnetic Lorentz force and impulsive thrusting for actuation. It is shown that the required amount of thruster actuation for formation keeping can be significantly reduced when used in concert with Lorentz force actuation.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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