Simulation and Analysis of PI and NN Tuned PI Controllers for Transformer Based Three-Phase Multi-level Inverter with MC-PWM Techniques
Bibliographic record
Abstract
The proposed work mainly deals with transformer-based three-phase Multi-Level Inverter (MLI) where the switches in MLI are controlled by Multi-Carrier PWM (MC-PWM) techniques. In this article, 48V DC input voltage is fed to 48/400V High-Voltage DC-DC boost converter which is controlled by Proportional-Integral (PI) and Neural-Network (NN) tuned PI controllers. 400V DC output from boost converter is connected to three-phase MLI where the MLI switches are controlled by three different types of MC-PWM techniques like Phase Disposition (PD), Phase Opposition and Disposition (POD) and Alternate Phase Opposition and Disposition (APOD). The overall system performance in terms of Total Harmonic Distortion (%THD) is analyzed and it is depicted that the proposed system under different modulation indices gives improved THD results with an NN tuned PI controller-based boost converter. The whole analysis is performed on the MATLAB\Simulink platform.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".