Distributed output regulation of switching multi‐agent systems subject to input saturation
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Bibliographic record
Abstract
In this study, we consider the distributed output regulation (DOR) problem of linear multi‐agent systems subject to input saturation with switching topology. Owing to the input saturation elements, the considered systems is non‐linear. It is natural to take the semiglobal frame for it which allows one to use distributed linear feedback controller. The basic problem is to design distributed feedback controller for the considered multi‐agent systems in order to have all agents to track an active leader and/or distributed rejection with disturbance signals. Both the leader and the disturbance signal are modelled as the exogenous system with different dynamics and unmeasurable variables. A systematic distributed linear design approach based on the solvability condition is proposed for the considered DOR problem.
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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 | 0.000 |
| 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 | 0.001 | 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