Performance Analysis of Switched Control Systems Under Common‐source Digital Upsets Modeled by MDHMM
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Bibliographic record
Abstract
This paper proposes the theoretical model to analyze the performance degradation of control systems subject to common‐source digital upsets. In this paper, a multidimensional hidden Markov model (MDHMM) is used to characterize the correlated upsets and reveals the relationship between complex environments and stochastic random digital upsets injected into the control systems. These digital upsets coming from artificial complex environments are operated on distributed redundant processing controllers. Furthermore, this paper develops the theoretical analysis model for performance degradation of control systems under common‐source digital interferences modeled by MDHMM. Theoretical estimations for different redundant configurations are analyzed. Then corresponding simulation verifications for a specific control system are also conducted in details and compared with the theoretical analysis results. These analyses can help to select an optimal redundant design and provide an example for control systems design. This analysis also helps to balance the performance of system, reliability of system, and costs of system design in applications.
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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