Model-based fuzzy control results for networked control systems
Why this work is in the frame
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Bibliographic record
Abstract
This paper discusses aspects concerning the design of model-based fuzzy controllers for Networked Control Systems (NCSs). The stability analysis is related to the characteristic equation of these control systems, where the variable time delays create numerical problems. These numerical problems are first briefly investigated, along with signal processing aspects concerning NCSs. The popular Hilbert-Huang transform is applied to smooth the signals and also the variable time delay, also called latency, due to the communication in the network. The design of Takagi-Sugeno-Kang Proportional-Integral-fuzzy controllers dedicated to temperature control applications is next carried out; the stability of fuzzy NCSs is guaranteed by computing the controller tuning parameters as solutions to linear matrix inequalities. Experimental results for a laboratory equipment that models a first-order plus time delay process are included to validate the theoretical findings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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