Feedforward/feedback control of an inverter-based compensator
Bibliographic record
Abstract
This research presents seven different control strategies for an inverter-based compensator used to achieve fast-acting reactive current compensation. Two feedforward schemes and five feedforward/feedback structures are analyzed. The first feedforward configuration uses phase-shift control (or simply [delta]-control) and results from shifting the fundamental component of a fixed pulse-width square wave an angle 8 with respect to the sinusoidal network voltage. The second feedforward scheme uses phase-shift/pulse-width control (or simply [delta]/[mu]-control) and allows, in addition to the phase-shift, a variation of the pulse-width parameterized by [mu]. One feedforward/feedback scheme uses phase-shift control and the remaining feedforward/feedback schemes use phase-shift/pulse-width control. A linearized average model that only considers the fundamental components of the circuit variables, and an exact model that takes into account all the non-linearities of the system are developed. The former model is suitable for control synthesis and stability analysis while the latter is used to benchmark the average model and to evaluate the effect of neglecting the higher-order harmonics. All the control structures are examined in dynamic conditions by analyzing the transition from a capacitive to inductive mode of compensation, and vice-versa. The feedforward structures are also evaluated under stationary conditions in inductive and capacitive compensation modes. The performance achieved by each control strategy is evaluated by examining the compensator's dynamic response, using performance measures. The simulation results indicate that the variation of the pulse-width enables keeping a constant link voltage, and that the best performance is achieved with the [delta]/[mu] feedforward/Is-feedback to [delta] control.
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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 | 0.000 |
| 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) | 0.002 | 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".