A comparative analysis of nonlinear current control schemes applied to a SEPIC power factor corrector
Bibliographic record
Abstract
In this paper, a comparative analysis of two nonlinear control schemes proposed for a single ended primary inductance converter (SEPIC) power factor corrector (PFC) is presented. The SEPIC converter, compared to conventional buck or boost ones, allows a low current ripple at the input for a relatively low level of the DC-bus voltage. Consequently, the high frequency filter needed at the AC-side of a buck converter is avoided, and the high voltage stresses applied on the switches are significantly reduced with respect to the boost converter. The converter is integrated at the DC-end of a single-phase diode bridge. In order to ensure a unity power factor at the AC-source side and a regulated voltage at the DC-load side, a multiple-loops feedback control scheme has to be developed. Two control strategies are considered in this paper. The first one uses a robust hysteresis current controller, whereas the other method is based on the application of the input/output feedback linearization technique on a state-space averaged model of the converter. In order to verify and compare the performance of both control schemes, numerical simulations are carried out on a switching-functions-based model of the converter, which is implemented using Matlab/Simulink. The proposed model of the converter is valid in the continuous current mode (CCM) and the discontinuous current mode (DCM). The control systems are tested under both rated and disturbed operating conditions. The systems performance is evaluated in terms of source current total harmonic distortion (THD), input power factor, DC voltage regulation and robustness toward a load disturbance
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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 | 0.000 | 0.001 |
| 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 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".