New Trends in Networked Control of Complex Dynamic Systems: Theories and Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In recent years, networked control systems (NCSs) have been extensively studied in both academy and industry and used in many fields, such as telerobotics, smart grids, intelligent transportation systems, and even in medical, military, and aerospace applications. NCSs offer great advantages, such as low cost, high reliability, simple installation and maintenance, and reduced weight and power requirements. In the meantime, the common shortcomings of the communication networks, such as transmission delays, packets drops and disorder, and data quantization, also appeared in the loops of the networked systems. During past decade, plenty of studies have been carried out in the literature to address the networkinduced problems for given dynamic systems that are relatively simple. However, more challenging mathematical problems such as network-based control of more complex dynamics, including time delay, parameter variations, uncertainties, and nonlinearities, are still largely open and necessitate further investigations to enable wider and more successful applications. This special issue aims to provide a timely discussion on the trends and challenges of networked control of complex dynamics systems. Both theoretical and application-oriented papers are sought for, addressing the issues and mathematical techniques of network-based control, sensing, multiagent control of complex dynamic systems, and so forth.
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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 | 0.001 |
| 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