Adaptive trajectory tracking control for VTOL‐UAVs with unknown inertia, gyro‐bias, and actuator LOE
Why this work is in the frame
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Bibliographic record
Abstract
Summary This paper proposes an adaptive controller for the trajectory tracking problem of vertical take‐off and landing unmanned aerial vehicles with unknown inertia and gyro‐bias, in the presence of external disturbances and actuator loss of effectiveness. To achieve our control objective, first, an a priori bounded virtual control law, providing an a priori bounded thrust and desired attitude, is designed for the translational dynamics. Thereafter, the torque input is designed for the rotational dynamics to track the desired orientation derived in the first stage. The stability of the overall hierarchical closed‐loop system and the global convergence of the tracking errors to zero are rigorously established. Finally, numerical simulations are performed to validate the effectiveness of the proposed control scheme.
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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 | 0.001 | 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 | 0.000 |
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