Design of a Nonlinear Hierarchical Adaptive Controller for a Novel Tilt-Rotor VTOL AquaUAV
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2021-1283.vid This paper presents the development of a novel tilt-rotor aquatic unmanned aerial vehicle that can land and take-off from water surfaces, namely AquaFly, with a focus on the controller design. The six degrees of freedom nonlinear equations of motion of AquaFly are derived through Newton-Euler formulation to capture the dynamics due to change in center of gravity location as a function of rotor tilt-angle. A nonlinear hierarchical adaptive control framework is proposed that consists of an outer-loop Total Energy based speed and altitude control cascaded with an inner-loop model reference adaptive attitude control. It is designed to cover all flight modes that include hovering, transition, and forward flight. The adaptive nature of the control framework allows compensation for modeling errors, uncertainties, and disturbances. Stability analyses are presented to show asymptotic tracking performance as well as the boundedness of all signals for the proposed control framework. Finally, simulation analyses are conducted and show control effectiveness for all flight modes.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".