Analysis of Urban Air Taxi Inner Loop Controller Architectures Subject to Noisy Inertial Measurement Unit Input while Immersed in Empirically-Developed Urban Airflow Disturbances
Bibliographic record
Abstract
This research work to assesses the influence of IMU noise on the attitude control of a generic Urban Air Taxi (UAT) flying in steady level-flight while immersed in urban airflow conditions, evaluates the performance of three inner-loop controllers, namely classical Proportional, Integral, Derivative (PID) control, Active Disturbance Rejection Control (ADRC) control, and Linear ADRC (LADRC) in the aforementioned flight conditions in terms of classical control metrics, passenger comfort and control surface power consumption. The grades of IMU are assessed in terms of their suitability for steady level-flight in this challenging environment and recommendations are drawn. The metrics used to gauge the performance of the controllers are used to recommend certain inner-loop control architectures for Urban Air Mobility (UAM). These recommendations are envisioned to assist certification authorities in developing the suitable regulations for UAM/UAT applications.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".