Event-Triggered Attitude Consensus of Multiple Rigid Body Systems With Prescribed Performance
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Bibliographic record
Abstract
The event-triggered almost global attitude consensus problem is considered in this article for multiple rigid body systems with prescribed performance. Two kinds of attitude consensus protocols using axis-angle vectors are proposed at the kinematic level with different prescribed performance constraints. The first protocol aims to achieve the event-triggered attitude consensus almost globally under jointly connected graphs. Based on a prescribed performance function with local states, the configuration space of parameterized attitude representations is shown to be positively invariant which almost globally covers . The second protocol is designed to reach attitude consensus with the prescribed transient behavior guaranteed in the event-triggered setting. By defining a prescribed performance function using the metric on axis-angle spaces, a dynamic event-triggered framework is designed to ensure both the attitude geometric topology constraint and prescribed convergence performance. Finally, numerical results are given to show the validness of the two control protocols.
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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 | 0.000 | 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 | 0.000 | 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