Enhancement of Drones’ Control and Guidance Systems Channels: A Review
Bibliographic record
Abstract
This paper describes a system and technique for controlling the attitude and direction of a quadrotor vertical take-off and landing unmanned aerial vehicle (VTOL UAV) using a horizontal thrust system (horizontal thruster), and hereby we call the system "Thruster Quad-rotor".The thruster quad-rotor operates by adjusting the rotational speed of each rotor's propellers to hold the quad-rotor's attitude (angular orientation and linear position in flight), while simultaneously control all direction horizontal motions in the horizontal plane using four thrusters installed on each arm of the quad-rotor.Each rotor is attached to an arm "tube".At the arm, on the tip, there is a thruster (electric duct fan -EDF).The four arms of the quad rotor are connected to the central body and aligned symmetrically at 45-degree angles to the X and Y axes forming a quad-rotor with "X" configuration.The horizontal thrusters enhance the effectiveness of the quad-rotor with novel design modifications; specifically, the horizontal thrusters increase the typical under-actuation to conventional quad-rotors.The application of the novel thruster concept leads to an increase in maneuvering of the UAV and an ability to resist winds and fly in tight spaces and scenarios, which presents flight's mission limitations.This paper will include the practicality of this new system, its conceptual and design aspects, and the mathematical modeling of the channels for the new UAV's enhanced control and guidance system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".