A Descriptor Approach to Robust Leader-Following Output Consensus of Uncertain Multi-Agent Systems With Delay
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
In this technical note, a descriptor approach to leader-following output consensus of multi-agent systems with both stationary and dynamic leaders is given in the presence of transmission delay and model uncertainty. The proposed method can deal with stable and unstable agents described by general linear models. To this end, a new proportional-derivative-integral (PID) consensus protocol for the closed-loop multi-agent system is proposed under a directed graph. Applying this consensus protocol to the multi-agent system leads to a time-delay closed-loop equation of neutral type. To deal with the resulting neutral system, a descriptor model transformation is used to derive delay-dependent sufficient conditions for the existence of the consensus protocol in terms of certain linear matrix inequalities (LMI). The application of the proposed method is illustrated in a teleoperation system. Simulation results are given to show the effectiveness of the proposed approach.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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