Active Fault-Tolerant Tracking Control of a Quadrotor UAV
Bibliographic record
Abstract
This paper presents a reliable active fault-tolerant tracking control (AFTTC) design method against actuator faults of a quadrotor unmanned aerial vehicle (VAV). The scheme consists of a baseline controller, a fault detection and diagnosis (FDD) estimator and an adaptive fault compensator. In the absence of actuator faults, a state feed-back controller acting as the normal controller is developed by utilizing linear quadratic regulator, so that the system stability and desired tracking performance are guaranteed. When the actuator fails to operate, an adaptive two-stage Kalman filter estimator is exploited for simultaneous state and fault estimation. Using the information from the FDD estimator, an adaptive fault compensator based on model reference adaptive control is designed automatically to mitigate the negative impacts of actuator faults. Simulation results show that the proposed AFTTC method enables the quadrotor UAV to track the desired refere-nce commands in the absence/presence of actuator faults.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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 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".