Closed‐loop design of fault detection for networked non‐linear systems with mixed delays and packet losses
Why this work is in the frame
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Bibliographic record
Abstract
This study is concerned with the problem of fault detection (FD) for networked control systems with discrete and infinite distributed delays subject to random packet losses and non‐linear perturbation. Both sensor‐to‐controller and controller‐to‐actuator packet losses are modelled as two different mutually independent Bernoulli distributed white sequences with known conditional probability distributions. By utilising an observer‐based fault detection filter (FDF) as a residual generator, the FD for networked non‐linear systems with mixed delays and packet losses is formulated as an H ∞ model‐matching problem. Attention is focused on designing the FDF in the closed‐loop system setup such that the estimation error between the residuals and filtered faults is made as small as possible and at the same time the closed‐loop networked non‐linear system is exponentially stable in the mean‐square sense. To show the superiority and effectiveness of this work, two numerical examples are presented.
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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