Adaptive Current Observer Design for Single Current Sensor Control in PMSM Drives
Bibliographic record
Abstract
A 3-phase permanent magnet synchronous machine (PMSM) drive system usually requires at least two current sensors for phase current measurements to achieve high performance control. When there is only one current sensor working in the drive system, accurate current observers are critical to ensure the control performance. In this paper, a novel adaptive current observer based single current sensor (SCS) control strategy is proposed. In the proposed approach, an augmented current state observer is built based on the PMSM dynamic equations with the consideration of machine parameter variation and system uncertainties. To ensure a good SCS control performance in the time-varying speed condition, a new computationally efficient methodology towards a desired pole-placement for the adaptive observer gain design is also proposed. More specifically, the proposed observer gains can be calculated analytically for the desired dynamic performance. Compared with existing methods, the proposed current observer has a straightforward gain design, and it further reduces current estimation errors and improves the robustness against machine parameter variation and system uncertainty. The proposed SCS control approach is validated with extensive experimental tests on a laboratory interior PMSM under both steady-state and transient conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".