Application of Multivariable Fuzzy Control for Large-scale Wind Turbine’s Rated Wind Speed
Bibliographic record
Abstract
The large-scale wind turbine system is a typical multivariable nonlinear system,and it reflected in the coupling effect between the pitch control loo Pand the torque control loop. Traditional control methods focus on single variable and ignore the coupling between loops. Therefore,in the real production,it can not achieve a good control effect. In this paper,the control over rated wind speed is based on multivariable fuzzy control,and the pitch controller and torque controller will be adjusted at the same time to ensure the rotational speed of the wind turbine is constant in the vicinity of rated speed while the output power is constant in the vicinity of rated power when the wind speed is higher than the rated wind speed. This method considers the coordinate control of the loops,and it achieves decoupling through fuzzy control and generates nonlinear control rate without accurate mathematical model,and it has good dynamic control performance. The simulation results show the effectiveness of the method proposed in this paper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".