Development and experimental validation of direct controller tuning for spaceborne telescopes
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.
Bibliographic record
Abstract
Strict requirements in the performance of future space-based observatories such as the Space Interferometry Mission (SIM) and the Next Generation Space Telescope (NGST), will extend the state-of-the-art of critical mission spaceflight-proven active control design. A control design strategy, which combines the high performance and stability robustness guarantees of modern, robust-control design with the spaceflight heritage of conventional control design, is proposed which will meet the strict requirements and maintain traceabil-ity to the successful controllers from predecessor spacecraft. Two principal tools are developed: an analysis algorithm that quantifies each sensor/actuator combination’s effec-tiveness for control, and a design engine which tunes a baseline controller to improve per-formance and/or stability robustness. The sensor/actuator effectiveness indexing tool requires a reduced-order state-space model of the plant. A modification of the balanced reduction method is introduced which improves numerical conditioning so that the order of large models of flexible spacecraft may be decreased. For each sensor and actuator an index is computed using the modal
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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