Actuator Fault Detection and Isolation for a Network of Unmanned Vehicles
Why this work is in the frame
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Bibliographic record
Abstract
This technical note investigates development, design and analysis of actuator fault detection and isolation (FDI) filters for a network of unmanned vehicles. It is shown that actuator fault signatures in a network of unmanned vehicles are dependent and the network can be considered as an over-actuated system. An isolability index mu is defined for a family of fault signatures and a new structured residual set is developed that is selectively capable of properly detecting and isolating mu multiple faults in linear systems with dependent fault signatures, such as over-actuated systems. Our proposed algorithm is then applied to the actuator FDI problem in a network of unmanned vehicles configured according to centralized, decentralized and semi-decentralized architectures. A comparative analysis in terms of the capabilities and limitations of these architectures is performed. Simulation results presented for the formation flight of multiple satellites demonstrate the effectiveness of our proposed FDI algorithm.
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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 | 0.000 | 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) | 0.000 | 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