Input/output feedback linearization control of a three-phase three-level neutral point clamped boost rectifier
Bibliographic record
Abstract
In this paper, the authors propose a new control strategy for a three-phase three-level neutral-point-clamped boost rectifier. It consists of applying a nonlinear feedback linearization technique. The nonlinear state space model of the rectifier was obtained in the (d,q,0) reference frame using the power balance between the input and output sides. The input/output feedback linearization is then applied and a linearizing control law is derived. Hence, the resulting model is linearized and decoupled. Afterwards, the tracking controllers are designed based on linear techniques to control line-currents, output and neutral point voltages. An integral action was added in order to robustify the controller with respect to parameter variations. This control uses a 3 kHz pulse width modulator. Computer simulations based on the use of Power System Blockset and Simulink/Matlab verify the robustness of the proposed control law in both balanced and unbalanced output load conditions. The line-current THD and output voltage ripples are very low. The settling time and the overshoot are quite small in comparison with standard PI controller.
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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 | 0.000 |
| 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) | 0.001 | 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".