High-Performance Motion Control of the METIS Cold Chopper Mechanism
Bibliographic record
Abstract
We present the main results of the performance test campaign of the Mid-Infrared European Extremely Large Telescope Imager and Spectrograph (METIS) Cold Chopper Demonstrator (MCCD). This tip/tilt mirror, which operates at a temperature of 77 K, is one of the critical components in the METIS for the European Extremely Large Telescope. The performance requirements of the MCCD relate to the field of fast and very accurate reference tracking. We discuss the applicability of different high-performance motion control strategies and describe the control synthesis of a repetitive and of a novel hybrid controller. We identified the presence of nonlinearities in the plant, which limits the performance of the hybrid controller. The repetitive controller shows very promising results and can handle the nonlinearities in the system. This experimental phase concludes the MCCD program, which was initiated to verify the feasibility of a high-performance cryogenic tip/tilt mirror at an early stage in the METIS development. Because of the very promising test results, no significant changes to the hardware will be implemented. We believe that minor adjustments will suffice to meet all requirements of the final hardware after integration with the METIS instrument.
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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 | 0.000 |
| 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 | 0.001 | 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".