A tunable fuzzy logic controller for chopper-fed separately excited DC motor drives
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Bibliographic record
Abstract
The paper presents a novel online tunable fuzzy logic controller (FLC) for the speed regulation of separately excited DC motor drives. FLC structure is implemented with linguistic classifications using a hybrid input of motor speed and current errors. The membership grade has been scaled (weighted) by a tuning factor in the defuzzifier stage of the FLC structure. The weighting factor is determined using a dynamic online rule-based scaling criteria of minimum speed excursion. In the defuzzification output stage, a modified "weighted center of area" technique is use to produce a crisp effective output to control the duty cycle ratio of the DC-DC chopper. The paper presents dynamic simulation results for a separately excited DC motor fed from a PWM DC-DC chopper. These results are obtained using the tunable fuzzy logic controller with an online adaptive variable defuzzifier structure and give good dynamic and robust response with minimum inrush motor current.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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