Multirate FCS-MPC for Parallel Dual-Converter-Fed PMSM Drives With Reduced Circulating Currents
Bibliographic record
Abstract
When implementing finite control set model predictive control (FCS-MPC) schemes in parallel converters sharing a common dc link, circulating currents become prominent due to the relatively low switching frequency. Although the multirate technique was proposed later to enhance the calculation efficiency, it is complex in parallel converters due to the numerous switching states and strong coupling between control variables. This article presents a multirate FCS-MPC method for permanent magnet synchronous machine (PMSM) drives fed by parallel converters. Reduced circulating currents are achieved from two primary aspects. First, the equivalent multilevel model of parallel converters is integrated with a multirate structure. This fully utilizes the redundancy in switching states, thus simplifying the calculation and enabling a higher equivalent control frequency. Second, the regulation of circulating currents is decoupled from the motor-side variables, allowing for precise regulation of circulating current and easy design of cost functions. In contrast to conventional modulation-based schemes, the proposed scheme ensures superior stator current performance and fast dynamic response under all operating conditions. The effectiveness of the proposed method was validated through experiments.
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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 | 0.001 |
| 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".