Fixed-time Event-Based Consensus Tracking for Networked Euler-Lagrange Systems with Limited-time State Constraint.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article focuses on the problem of fixed-time consensus tracking (FTCT) for limited-time state-constrained networked Euler-Lagrange (NEL) systems subject to the limited communication and computation capacities. To enable each follower to estimate leader information under unidirectional and intermittent communication environments, an event-based fixed-time distributed observer (FTDO) is constructed, while excluding Zeno behavior from the analysis. Subsequently, to reduce the control input update frequency and consumption, a backstepping-based adaptive event-triggered local control (AETLC) strategy is proposed, which ensures practical fixed-time convergence for all errors and eliminates Zeno behavior. Specifically, a novel limited-time constrained function with a unique shift function is developed, which is capable of uniformly handling limited-time constraint, persistent constraint, and unconstrained cases without altering the control structure. Simulation results are eventually performed to validate the suggested methodologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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