A rule-based fuzzy logic controller for a PWM inverter in photo-voltaic energy conversion scheme
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Bibliographic record
Abstract
A rule-based controller based on fuzzy set theory for controlling the output power of a pulse width modulation (PWM) inverter in a photovoltaic (PV) energy conversion interface scheme is presented. The objective is to track and extract the maximum available solar power from the PV array under varying solar insolation levels. To achieve this the power error and the rate of change of this error are used as input signals to the fuzzy rule-based controller and its output signal is used to control the PWM inverter. The input error signals are fuzzified and expressed as linguistic labels characterized by their membership grades. Using a fuzzy relation matrix, a set of 49 rules find fuzzy logic operations, the controller output is obtained. The fuzzy controller output expressed in linguistic labels is defuzzified to obtain the actual analog signal to control the PWM inverter. The proposed fuzzy rule-based controller is simulated and experimentally verified, and is found to give good power tracking performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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) | 0.001 | 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) | 0.001 | 0.000 |
Machine scores (provisional)
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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