A New State-Space Nonlinear Control Approach of a Doubly Fed Induction Motor Using Variable Gain PI and Fuzzy Logic Controllers
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Bibliographic record
Abstract
In this paper, the authors are interested on the field-oriented control with variable gain PI (VPGI) and fuzzy logic regulators of doubly fed Induction Motor (DFIM) fed by two PWM inverters with separate DC bus link. By introducing a new approach for decoupling the motor’s currents in a rotating (d-q) frame, based on the state space input-output decoupling method, we obtain the same transfer function (1/s) for all four decoupled currents. Thereafter and in order to improve the performances of the machine’s control, the VPGI and fuzzy logic controllers with seven subsets were used for the regulation speed. The Results obtained in Matlab/Simulink environment show well the effectiveness of the technique employed for the decoupling and the speed regulation of the machine.
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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 | 0.000 | 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