Trajectory Tracking Control of Highly Maneuverable Fixed-Wing Unmanned Aerial Vehicles
Bibliographic record
Abstract
Agile fixed-wing aircraft combine the fast and efficient characteristics of conventional fixedwing platforms with the high maneuverability and precision of rotorcraft. To expand their range of application, a key challenge is the development of control systems that harness this increased maneuverability, with the goal of enhancing or expanding the possible motions of conventional fixed-wing flight. Thiswork presents a control architecture that enables agile fixedwing platforms to track a time-parametrized, three-dimensional position trajectory which is unconstrained by common limitations arising from an aircraft kinematic model assumption, including minimum airspeed, heading rate, and climb rate. The proposed system is a cascaded controller designed in two parts. First, a singularity-free, quaternion-based inner attitude control loop is designed to track attitude references. Then, an outer position control loop is constructed to determine the required thrust force and reference attitude that will drive the inertial position errors to zero. This outer loop is a hybrid controller, consisting of a control strategy for the steady regime and another for agile maneuvers. A switching logic is derived to ensure that any change of position controller occurs when the two stability regions overlap, retaining stability for the overall system. The resulting controller does not require any attitude reference to perform aggressive maneuvers, greatly simplifying the trajectory generation problem. Controller performance is first verified through numerical simulation using a high-fidelity aircraft model. A Software in the Loop simulation, which accounts for sensor noise, state estimation, and discrete-time implementation of the control algorithm, is performed before finally implementing the control system on a physical platform. Preliminary results show the control system enables the aircraft to perform a series of maneuvers often deemed infeasible for fixed-wing aircraft, thus greatly enhancing the usefulness of the platform.
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.
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 | 0.000 |
| 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) | 0.001 | 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".