STABLE MODEL IDENTIFICATION OF DYNAMICS IDENTIFICATION AND CONTROLS EXPERIMENTS (DICE)
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
System identification is often a precursor to model-based control system designs that assume the plant dynamics to be controlled are known. Many system identification algorithms, such as Observer Kalman Filter Identification (OKID), do not guarantee that the identified model will be stable and when applied to flexible structures that exhibit rigid modes, the identified models are often unstable. These unstable models can create problems for model validation and subsequent model order reduction for control design. By exponentially curve fitting the unstable Markov parameters generated by OKID, this instability can be effectively identified and removed allowing stable models to be identified. This system identification technique is validated by computer simulation as well as experimentally using the Dynamics Identification and Control Experiment (DICE), a flexible spacecraft emulator designed to fly on the NASA space shuttle.
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) | 0.000 | 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