Nonlinear control of three-phase three-level four-wire NPC converter
Bibliographic record
Abstract
This paper presents a new approach of input-output feedback linearization control applied to the three-phase three-level four-wire neutral point clamped (NPC) converter. Under the proposed control strategy, the NPC converter demonstrates the capability to achieve simultaneously two tasks. The first task is to operate as a nonpolluting rectifier by regulating and nearly equalizing the two dc capacitor voltages while providing power to the dc loads. It is worthy of note that the voltage imbalance between the upper and lower capacitors and the neutral current represent a well-known problem in the three-level NPC converters. As a second task the NPC converter will behave as a shunt active power filter (SAPF) to compensate current harmonics, unbalances and reactive power produced by a combination of single-phase and three-phase nonlinear loads connected at the point of common coupling on the grid. The multivariable state space model of the NPC converter in the dq0 synchronous reference frame is used to design the nonlinear controller which is based on the input-output feedback linearization. It is shown that the model zero-dynamics is asymptotically stable ensuring the local stability of the internal dynamics. The proposed control strategy applied to the NPC converter is verified by computer simulations. The system stability is confirmed under severe dynamic changes in the operation conditions. The results of conducted simulations validate the viability and effectiveness of the NPC converter to maintain grid side currents balanced and near sinusoidal with unity displacement power factor. The simulation results also confirm the capability of the NPC converter to stabilize the dc voltages while supplying unbalanced dc loads.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".