Event-Triggered Model Predictive Control for Compartmental Systems with Application to Congestion Control of Air Traffic Networks
Why this work is in the frame
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Bibliographic record
Abstract
Air traffic management aims to mitigate congestion in air traffic networks mainly caused by capacity constraints of air centers. In this paper, an air traffic network is effectively modeled as a compartmental system, and a model predictive control (MPC) approach with a steady state-input constraint is proposed to mitigate traffic congestion and achieve the departure demand as best as possible. An event-triggered scheme is designed to trigger the solution of the MPC optimization problem when necessary, leading to reduced computational and communication burden. Recursive feasibility of the proposed approach and asymptotic evolution of the system to a steady point are analyzed. The effectiveness of the proposed approach is demonstrated by a five-inflow and three-outflow air traffic network with ten air centers.
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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