Performance and Lyapunov Stability of a Nonlinear Path Following Guidance Method
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.837
- Threshold uncertainty score
- 0.752
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.223 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Performance and stability are demonstrated for a nonlinear path-following guidance method for unmanned air vehicles. The method was adapted from a pure pursuit-based path following, which has been widely used in ground based robot applications. The method is known to approximate a proportional-derivative controller when following a straight line path, but it is shown that there is also an element of anticipatory control that enables tight tracking when following curved paths. Ground speed is incorporated into the computation of commanded lateral acceleration, which adds an adaptive capability to accommodate vehicle speed changes due to external disturbances such as wind. Asymptotic Lyapunov stability of the nonlinear guidance method is demonstrated when the unmanned air vehicle is following circular paths. The adaptive nature of the guidance method makes its stability independent of vehicle velocity. The stability analysis is also extended to show robust stability of the guidance law in the presence of saturated lateral acceleration, which is an inherent limitation of flight vehicles. Flight tests of the algorithm, using two small unmanned air vehicles, showed that each aircraft was controlled to within 1.6 m root mean square when following circular paths. The method was used to perform a rendezvous of the two aircraft, bringing them into very close proximity, within 12 m of along track separation and 1.4 m root mean square relative position errors.
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.
The record
- Venue
- Journal of Guidance Control and Dynamics
- Topic
- Guidance and Control Systems
- Field
- Engineering
- Canadian institutions
- Bombardier (Canada)
- Funders
- not available
- Keywords
- Control theory (sociology)Lyapunov functionNonlinear systemStability (learning theory)Path (computing)Lyapunov redesignLyapunov equationComputer scienceMathematicsPhysicsControl (management)Artificial intelligence
- Has abstract in OpenAlex
- yes