Immersion and Invariance Adaptive Control for Proximity Operations under Uncertainties and Modeling Errors
Why this work is in the frame
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Bibliographic record
Abstract
Two Immersion and Invariance (I&I) adaptive controllers are designed for translational trajectory tracking in spacecraft proximity operations under unknown mass properties and unmodeled dynamics. In one case, the controller is designed utilizing the Clohessy-Wiltshire dynamics, requiring known mass bounds and I&I extension methods such as filtered-states and dynamic scaling factors. For the second case, the I&I controller is developed by approximating the exact nonlinear relative dynamics as double-integrator dynamics through assumptions such as short time scales relative to one orbital period, and small relative distances compared to an orbital radius. These simplified dynamics allow for an analytical I&I controller without assumed bounds on mass, or any extension methods. Simulations are presented which show that the designed I&I estimators converge nearly precisely to the actual mass value, regardless of higher-order dynamical modeling errors. In addition, simulation comparisons to standard adaptive techniques such as Indirect Regressor-Matrices and Direct Simple Adaptive Control show improved transient performance and reduced control effort. The I&I controller developed under double-integrator dynamics is computationally light requiring only one numerically solved state and two analytical equations, making itwell-suited for on-board real-time applications.
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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