Application of the New Quasi-Linear Control Theory to the AC Current Shaping and DC Voltage Regulation of a Three-Phase boost-type AC/DC Vienna Converter Under Very Severe Operating Conditions
Bibliographic record
Abstract
In the present paper, design and numerical implementation of a multi-loops quasi-linear control technique is proposed for a three-phase three-level boost-type AC/DC Vienna converter. Acquiring high stability and perfect rejection of disturbances and initial conditions, the lately introduced quasi-linear theory is very suitable for power electronic circuits, subjected to diverse operating disturbances and parametric changes. Inner feedback loops ensures dq currents tracking and cross-decoupling cancellation with respect to the dq control inputs, thus adequately controlling the power flow from the grid to the load. In the same inner loop, the zero-sequence component of control inputs ensures the symmetry of split DC bus voltages. The obtained dqo components for control variables, transformed into their abc equivalents to generate the converter switches duty cycle profiles, are, thereafter, pulse-width modulated, thus yielding the I.G.B.Ts gating signals. The outer voltage loop is designated to ensure total DC voltage regulation by adjusting the magnitude of the current reference for the inner current loops. The proposed control strategy is based on a previously established and experimentally validated small signal model, expressed in the dqo reference frame. At a first stage, the proposed theoretical control approach is simulated using the converter switching function model built on SIMULINK/ Matlab. Then, the proposed control scheme is experimentally validated on a 1.5 k W laboratory prototype using the DS 1104 controller board of dSPACE. Low AC line currents total harmonic distortion (THD), unity power factor (PF) operation and regulated split DC bus voltages are achieved, for a wide clan of operating conditions, including severe utility and load disturbances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".