Refined Safety Control of Unmanned Flight Vehicles via Fractional-Order Calculus
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
The monograph explores the safety of unmanned flight vehicles via the corresponding fault-tolerant control design methods. The authors analyse the safety control issues of unmanned flight vehicles, which include finite-time recovery against faults, concurrence of actuator faults and sensor faults, concurrence of actuator faults and wind effects, and faults encountered by a portion of unmanned flight vehicles in a distributed communication network. In addition, the commonly used simple but effective proportional-integral-derivative structure is also incorporated into the safety control design for unmanned flight vehicles. By using the fractional-order calculus, the developed safety control results are able to ensure flight safety and achieve the refined performance adjustments against faults and wind effects. The book will be of interest to 3rd/4th year undergraduate students, postgraduate and graduate students, researchers, academic staff, engineers of aircraft and unmanned flight vehicles.
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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) | 0.001 | 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 | 0.001 |
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 it