Steady-state Invariant Kalman Filter for Attitude and Imbalance Estimation of a Neutrally-buoyant Airship
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Bibliographic record
Abstract
This paper presents the development of an algorithm to estimate the state of a neutrallybuoyant airship as well as its deviation from a perfect mass-balance. That is to say, the eccentricity of the center of mass with respect to the center of buoyancy and the difference between the mass of the system and that of the displaced fluid are estimated. The algorithm is based on a discrete-time invariant Kalman filter which is cast as a steadystate Kalman filter by using symmetry-preserving properties, and then, the eccentricity and mass deviation are incorporated as partially coupled to the state estimation using an assumption of settled estimation covariance, i.e., the main assumption of a steady-state Kalman filter. Experimental results show the use of those additional estimated quantities to correct steady-state regulation errors of a symmetry-preserving LQR control law, as a viable adaptive dynamics compensation on the position and attitude control.
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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