A Redundant Aircraft Attitude System Based on Fuzzy Logic Data Fusion of the Miniaturized Inertial Sensors
Bibliographic record
Abstract
A redundant strap-down attitude system using three miniaturized gyro sensors linear clusters in the detection unit are here presented. For each of the three clusters the inertial sensors' data are fused by using a fuzzy logic method, in order to improve the angular speed signal measured by the detection unit and delivered to the attitude algorithm. After a short introduction the data fusion algorithm and the theoretical background of the attitude system are shown in the sections two and three. In the fourth section, the software implementation and experimental validation of the redundant inertial attitude system are exposed. To perform the experimental validation of the developed redundant attitude system some data were simultaneously acquired from a three-dimensional redundant gyro sensors unit and from an integrated INS/GPS navigator; the INS/GPS system was used as reference system to perform an evaluation of the attitude angles errors. The three-dimensional redundant gyro sensors unit was built with twelve gyros disposed in three clusters of four sensors each, along the x, y and z axes of the body frame.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".