Finite-Time Guidance and Control for Uncrewed Receiver Aircraft in Aerial Refueling Rendezvous
Bibliographic record
Abstract
This paper investigates a problem of autonomous aerial refueling point parallel rendezvous guidance and flight control subject to exogenous wind field disturbances. The tanker and uncrewed receiver aircraft approach the common refueling rendezvous point according to their respective flight plans, ultimately maintaining a fixed altitude and the same speed. According to the relative position of refueling target point and uncrewed receiver, a new continuous terminal sliding-mode guidance law combined with the prescribed performance control theory is designed under the end angle and speed constraints. Meanwhile, a finite-time observer is proposed to estimate the parameter uncertainties and wake vortex disturbances during refueling rendezvous. Based on the estimated information, a backstepping double-integral sliding-mode controller is developed for the uncrewed receiver flight control system. In the process of the guidance and flight control system, the integral variable is introduced to improve the steady-state performance. The designed guidance and control system can enable the uncrewed receiver to achieve the refueling rendezvous task within finite time and improve the efficiency of uncrewed aerial refueling. Comparative numerical simulations are provided to demonstrate the effectiveness of the proposed guidance and control scheme.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".