Flight Control Modeling and Integration from a Real-Time Systems Simulator to a Flight Training Device
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
Simulation is an important tool in control system design. Real-time simulation of flight controllers for the GARTEUR designed RCAM challenge was previously conducted on the University of Toronto Institute for Aerospace Studies real-time systems simulator (RTSS). As a next step to the controller design and simulation problem, it was desired to test a controller in the flight training device (FTD), which presents a more complex and realistic aircraft model, as well as offering a different visual perspective. The FTD runs on a commercial simulation software package called FLSIM. This project consisted of transferring two controllers from the RTSS to a FLSIM module. In order to duplicate the RCAM landing approach, the trajectory generator was also transferred. All other systems, such as flight dynamics and control actuators, were modeled by FLSIM. Through this exercise, a procedure for transferring models from the RTSS to the FTD was developed. Furthermore, it was found that controllers developed in the RTSS function in the FTD environment, but require tuning to achieve optimal results due to the more complex operational environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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