Selective Harmonic Elimination in Space Vector Modulated AC–AC Converter Using FPGA
Bibliographic record
Abstract
Controlling converters by FPGA based system is a challenging problem because of the strict real time constraints. Nonetheless, FPGA has been applied to a wide variety of applications. This paper proposes an FPGA implementation of a particle swarm optimization (PSO) based selective harmonic elimination space vector pulse-width modulation (SHE-SVPWM) in an AC–AC converter. The present approach is utilized to generate a variable frequency high quality AC output from AC to AC converter with reduced THD and improved power quality. The objective function is formulated to ensure attainment of both sinusoidal output and reduction in THD simultaneously by incorporating a weight factor in the objective function. Harmonics up to the 13th order are attenuated by solving transcendental equations. Due to multiplicity of solutions, heuristic techniques are favored. PSO is used in offline mode to calculate the combination of switching angles and stored in look-up table, which makes easier to generate PWM signal in real time for the AC to AC converter. Experimental results are carried out to justify the performance and superiority of the present approach compared to conventional SVPWM and GA-SVPWM. An experimental prototype was developed with single phase induction motor load and test results are presented to validate the proposed design of the system.
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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) | 0.000 | 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)
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".