Distributed Time-Varying Formation Control for Multiagent Systems With Directed Topology Using an Adaptive Output-Feedback Approach
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Bibliographic record
Abstract
This paper addresses fully distributed formation control problems for high-order linear multiagent systems (MASs) with directed communication topology. In order to overcome the shortcomings of designing time-varying formation (TVF) protocols via the global information of the communication network and the full states of all the agents in existing formation results, a novel adaptive TVF protocol is developed. First, dynamic output feedback information and sequential observers are used to construct the adaptive TVF protocol. Then, a distributed algorithm which includes a TVF feasibility constraint is proposed. Only local outputs of neighboring agents are used in the algorithm. Moreover, applying the proposed approach and the Lyapunov stability theory, it is found that the fully distributed TVF can be achieved. Finally, numerical simulations are given to demonstrate the theoretical results.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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