Neighboring Optimum Feedback Control Law for Earth-Orbiting Formation-Flying Spacecraft
Bibliographic record
Abstract
Thispaperdevelopsafeedbackcontrollawthatguaranteesneighboringfuel-optimalityofthereconfigurationofa formation of Earth-orbiting formation-flying spacecraft. It aims for the case in which a specific formation is to be achieved at a specific true anomaly. It guarantees neighboring fuel-optimality of such a reconfiguration maneuver, assuming that the formation evolves in the vicinity of an uncontrolled reference trajectory. It is in the semi-analytic form,as onlyone time-varyinggain matrixneedstobecomputed beforethe maneuver. Itallows afuel consumption/ formation accuracy tradeoff with the selection of only one scalar gain. Simulations compare the performance of this controller with the linear-quadratic regulator and the mean orbit elements controller in the context of a 1 km size formation reconfiguration. Simulations show that this neighboring optimum controller can perform the maneuver with better accuracy while spending as much or less propellant than the other controllers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".