Strategy and Algorithms of Piloted Wig-Craft Automatic Control at Possible Failures of Primary Sensors
Bibliographic record
Abstract
The paper describes the method of providing the save flight control of piloted WIG-craft (ekranoplane) at possible failures of a part of primary sensors. The structural redundancy in the number of altimeters and inertial sensors permits to estimate a failure of any one sensor and indicate it to pilot for making decision about continuation of flight. Unfortunately, any sensor failure detection requires some time and during this interval the errors of altitude, roll and pitch measurements grow up significulty. The pilot can interfere in this process and speed up the making of the right decision both for detecting a failure and for arranging the safest flight mode after detecting a failure of one sensor.Proper coordination of the pilot's dynamics as a link in the automated control system and the dynamics of other elements of the control loops is of great importance to ensure the flight safety. The problem is especially relevant for WIG-craft in which due to the extremely low altitude of flight, an emergency situation at any failure develops very quickly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".