Fault tolerant shape control for output PDFs tracking of stochastic distribution systems
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Bibliographic record
Abstract
This paper investigates the fault-tolerant shape control (FTSC) problem for stochastic distribution systems. The available information for the addressed problem is the input and the measurable output Probability Density Function (PDF) of the system. The system is subject to actuator faults. In this case, the main objective is to achieve fault-tolerant shape control so that the output PDF can track a given target PDF shape even in the presence of faults. In this framework, an effective novel FTSC strategy is proposed based on the online estimation of the actuator faults, which includes a normal control law and an adaptive compensation control law simultaneously. The former can track the given output PDF with optimized performance index in the fault-free case, while the latter can automatically reduce (or even eliminate) the impact of faults for the given PDF shape. Finally, the effectiveness of the proposed design method is illustrated via a numerical example.
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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