On the leader-follower synchronization of Euler-Lagrange systems
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Bibliographic record
Abstract
In this paper we study the leader-follower synchronization problem of networked uncertain Euler-Lagrange systems under directed interconnection graphs. We first consider the case of ideal communication between agents and present an adaptive distributed control algorithm such that a group of Euler-Lagrange systems asymptotically synchronize their states to those of a dynamic leader with a time-varying trajectory. Then, we propose a modified design that achieves the same control objective under the assumption of intermittent discrete-time communication in the presence of varying communication delays and possible packet dropout. It is shown that leader-follower synchronization is achieved under sufficient conditions that can be realized uniformly of the interconnection topology between agents for a given characteristics of the communication process. Simulation results are given to illustrate the effectiveness of the proposed control scheme.
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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