Modelling and Multivariable Control Techniques for Small Coaxial Helicopters
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
ight of small coaxial helicopters ( < 70cm rotor diameter) poses signicant challenges in terms of comprehensive yet computationally feasible modeling and control. The coaxial platform provides several advantages at small scales in terms of size, footprint, eciency and stability. This study compares techniques used for the modeling and control of such an aircraft in order to identify a viable control design for an experimental platform. Models of the various thrust, servo and motor dynamics are presented, and the delity of the model is assessed. In terms of control techniques, linear methods such as PID, LQR and H1 mixed synthesis are presented. PID control is generally found to be ineective in most cases including trajectory tracking and disturbance rejection. LQR and H1 control techniques outperform PID in this regard and provide respectable results. Furthermore, the H1 control scheme is especially eective in achieving tighter trajectories.
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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) | 0.000 | 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 it