Optimal Distance-Based Formation Producing Control of Multi-Agent Systems with Energy Constraints and Collision Avoidance
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Bibliographic record
Abstract
This paper considers the problem of an optimal distance-based formation producing control for multi-agent systems. We use the rigid graph theory in combination with the state-dependent Riccati equation (SDRE) method to develop a multi-agent formation producing scheme. We define a normalized rigidity matrix and use it for the rigorous stability analysis. A quadratic-like cost functional is defined that takes into account the cost of the formation as well as the energy cost. The proposed control law asymptotically minimizes the cost functional while it assures local asymptotic stability of the closed-loop system. Furthermore, we propose a solution for the global asymptotic stability and collision avoidance. In order to verify and validate theoretical results, we present several simulation results in both 2-D and 3-D spaces.
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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 | 0.001 |
| 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