A Novel Neuro-Fuzzy Based Field Oriented Control Scheme for Wind Energy Conversion Systems with Reduced Computation and Improved Performance
Bibliographic record
Abstract
Wind energy conversion system (WECS) requires improved dynamic & transient responses as it has to operate in uncertain wind speed conditions as well as to manage the system non-linearities. The classical proportional integral (PI) based control approach is not appropriate to tackle the non-linearities and uncertainties associated with the WECS. Therefore, A neuro fuzzy (NF) based field-oriented control (FOC) technique for WECS is designed and analyzed in this study. The designed NF based FOC scheme utilizes simplified NF networks for processing which has reduced computational steps considering the conventional NF based controllers used in WECS. The proposed NF based FOC scheme process the error related to -q axis stator side current and produce the gate pulses for the machine side converter. The presented FOC exhibits satisfactory dynamic and transient performances with reduced computations compared to the classical NF based FOC scheme. In addition, the responses of the simplified NF based FOC is superior considering the PI controller. The functionality of the proposed NF based FOC is verified through simulation and real time experimental analysis using DS 1104 platform in the laboratory.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".