Multi-Agent Modeling of Cyber-Physical Systems for IEC 61499 Based Distributed Automation
Bibliographic record
Abstract
The traditional industrial automation systems developed under IEC 61131-3 in centralized control are statically programmed with determined procedures to perform predefined behaviors/tasks in structured environments. A major challenge for the traditional system is the frequent changes and constant uncertainties of the system itself, its operations and the operating environments. Therefore, in this paper we are trying to develop a two-layer architecture for modelling industrial cyber-physical systems, in which the multi-agent computing model is designed for the high-level architecture and the IEC 61499 function block model is applied for the low-level architecture. It aims to integrate system intelligence by communicating and computing cores from the high-level cyber modules and real-time adaptation by distributed and intelligent control of the low-level physical modules. The proposed modeling framework is tested for the feasibility study through preliminary experiments on Jetson Nano and Raspberry Pi by using agent modeling tool SPADE and function block modeling tool Eclipse 4diac.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".