Formulation of Torque-Optimal Guidance Trajectories for a CubeSat with Degraded Reaction Wheels
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the theory and design of a torque-optimal guidance algorithm for CubeSat applications. CubeSats and nano-satellites provide mission-exible low-cost platforms for the academic and scientic communities to conduct cutting-edge research in the harsh environment of space. The mission life of nano-satellites may be limited by the attitude actuators, and it is therefore benecial to reduce torque and angular momentum usage during reorientation maneuvers. The algorithm focuses on being computationally lightweight and robust, while including the eects of gyroscopic moments, environmental torques, and degraded reaction wheels. Results indicate that this torque-optimal guidance algorithm demonstrates substantial improvements in performance and pointing accuracy over an Eigenaxis controller for similar maneuvers, with low to moderate computational overhead. In doing so, it presents a signicant advancement towards the development of intelligent GN&C systems for small satellites.
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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