Robust Guidance for a Reusable Launch Vehicle in Terminal Phase
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
This article focuses on the 3-D guidance strategy for a reusable launch vehicle (RLV) during terminal area energy management (TAEM) phase. Based on sliding-mode and shrinking-horizon techniques, the proposed scheme consists of trajectory generation and correction mechanisms, which can enhance the guidance precision and robustness against disturbances. The RLV guidance model, in the form of a set of highly nonlinear differential equations in the time domain, is recast as an altitude-domain model. By this means, the main characteristics of TAEM gliding motion are extracted. The altitude-domain model is thereby used for trajectory generation. A sliding surface and a guidance law are proposed. Hybrid TAEM constraints can be fully satisfied when the proposed guidance law drives the altitude-domain vehicle model to the designated altitude. Using the proposed guidance law as the input of the altitude-domain model, a constrained TAEM trajectory is generated, leading to TAEM guidance commands simultaneously. The commands are utilized to drive the time-domain model to the terminal target. In an attempt to compensate for model uncertainties and initial deviations, the guidance commands are modified periodically by the shrinking-horizon correction mechanism according to current states. Simulations on different scenarios are provided to demonstrate the performance of the proposed guidance strategy.
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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