Design of an Artificial Neural Network Control Based on Levenberg-Marquart Algorithm for Grid-Connected Packed U-Cell Inverter
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Bibliographic record
Abstract
In this paper an Artificial Neural Network (ANN) controller based on Levenberg-Marquart algorithm is designed and applied to a five-level sensor-less Packed U-cell (PUC5) inverter operating as grid connected mode. The advantage of the proposed design is that there is no longer required to the conventional parameters tuning snag confronted with the traditional Proportional Integral (PI) method. An offline algorithm takes in action of the controller parameters tuning calculation. The proposed ANN regulates the grid line current while the DC bus voltage is maintained constant with no need of regulator as the capacitor is self-voltage balanced in PUC5 topology. The overall design is simple as less tuning, sensors and regulators are requested compared to the conventional PI compensator case. Simulation results on MATLAB/Simulink are conducted to validate the performance of the controller in both steady and dynamic state where low Total Harmonic Distortion (THD) of the line current and high dynamic system response can be identified.
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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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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