Specified-Time Distributed Control for Multiagent Systems Over Undirected and Directed Graphs: A Linear Operator Theoretic Framework
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Bibliographic record
Abstract
This article focuses on the performance analysis of distributed controllers for general linear multiagent systems in the sense of convergence time and energy consumption. First, the specified-time optimal controller is obtained using the linear operator theory-based method, and then the optimal topology is deduced. Second, to analyze the impact of communication topology on energy consumption, two distributed, suboptimal specified-time controllers are developed for undirected and directed graphs, respectively. By utilizing the inverse optimality method and Lyapunov function scaling, the performance in terms of the bounds of the gaps between the energy consumption of the suboptimal and optimal control laws is derived, which evaluates the effectiveness of the suboptimal controllers. Finally, as the simulation results show, the performance can specify appropriate settling times for applications with different energy budgets and facilitate optimizing the communication topology to reduce the energy gap.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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