A Self-Triggered Impulsive Approach to Group Consensus of MASs With Sensing/Actuation Delays
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Bibliographic record
Abstract
This article presents a self-triggered impulsive framework for group consensus of multiagent systems (MASs). Two types of self-triggered delayed impulsive control schemes are proposed to regulate impulsive protocols with sensing and actuation delays, respectively. Here, the Lyapunov-based and comparison-system-based approaches are constructed to achieve the iterative updates of impulse sequences with flexibility, especially the upper bound or average interval of impulsive periods is not restricted explicitly. In addition, several sufficient criteria for multigroup consensus of MASs with sensing and actuation delays are presented, where the correlation inequalities between trigger parameters, time delays, and control strengths are established to promote the co-design of impulsive controller and self-triggering algorithm. The Zeno behavior could be successfully eliminated. It is shown that the presented self-triggered schemes do not necessitate continuous or periodic event-detections and the interaction for neighboring agents works in an impulsive manner, which significantly saves the resource consumption of communication and control. Finally, two numerical examples illustrate the effectiveness of the proposed schemes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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