Nussbaum-based fractional-order sliding-mode fault-tolerant cooperative control of multiple UAVs with event-triggered mechanism
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Bibliographic record
Abstract
To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles (UAVs), and reduce the communication and computational resource consumption of multiple UAVs, a Fraction-Order (FO) sliding-mode Fault-Tolerant Cooperative Control (FTCC) strategy is proposed for multiple UAVs based on Event-Triggered Communication Mechanism (ET-COM-M) and Event-Triggered Control Mechanism (ET-CON-M). First, by considering the limited communication bandwidth of multiple UAVs in formation, an ET-COM-M is designed to significantly reduce communication times. Then, a distributed observer is skillfully constructed to estimate the reference signals for follower UAVs. Moreover, the adaptive strategy is incorporated into the Radial Basis Function Neural Network (RBFNN) to learn the lumped unknown terms for handling bias actuator faults and parameter uncertainties. Besides, the Nussbaum method is used to deal with the loss-of-effectiveness faults. To further achieve the refined control performance against faults, FO calculus is artfully integrated into the sliding-mode control protocol with ET-CON-M. Finally, Zeno behavior is excluded by rigorous theoretical analysis and Lyapunov stability is proved to show the effectiveness of the designed FTCC strategy. Simulation results show that the designed FTCC strategy with Event-Triggered Mechanism (ETM) can guarantee the safety of multiple UAVs and simultaneously reduce the communication and control frequencies, making the developed control scheme applicable in engineering.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it