Distributed control of formation flying spacecraft using deterministic communication schedulers
Why this work is in the frame
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Bibliographic record
Abstract
This paper is concerned with the formation flying control of spacecraft using a distributed architecture. Each agent uses an estimate of the formation state to compute its own actuation command. A simple deterministic scheduling strategy is first adopted for updating the estimates over a delayed data network, and the stability analysis is provided subsequently. A scheduling method for balancing the communication load among the agents is also proposed. It is assumed that different agents are coupled through their dynamics, as well as their control objectives, and that the output of each agent must track a desired reference input. Furthermore, an (open-loop) approximation of the parameter variation of the system is carried out throughout the control operation to improve the accuracy of state estimation. Simulations are given for a group of three spacecraft flying with leader-follower structure in deep space, and demonstrate the efficacy of the proposed scheme.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it