Optimal trajectory design of a deorbiting electrodynamic tether system
Bibliographic record
Abstract
This paper studies the optimal control problem of a nano-satellite deorbiting by a short electrodynamic tether. The optimal control theory is introduced by forming the control problem as a cost index minimisation subjected to several constraints. A direct method based on Hermite-Simpson discretisation is adopted to solve the constraint cost minimisation problem, resulting in an optimal trajectory including the time history of the states and control input, which achieves best deorbiting efficiency and libration stability simultaneously under the given mission requirements. In order to reduce the computation efforts, the continuous deorbiting process of an electrodynamic tether is discretised into a sequential time intervals, where during each interval the slowly varying orbital parameters of the electrodynamic tether are assumed constant. Thus, the whole optimal trajectory is obtained by combining the solutions to the optimal control problems in the intervals. Numerical simulations are performed to test the performance of the optimal trajectory by applying the control input profile to an electrodynamic tether under complex environment perturbations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".