Dynamical Delay Unification of Disturbance Observation Techniques for PMSM Drives Control
Bibliographic record
Abstract
The necessity of rejecting the external disturbance and model uncertainty is vital for control design to achieve high performance and robustness of the system. Disturbance cancelation techniques are, therefore, of interest for both academic and industrial research and development. Among them, disturbance observer based control (DOBC) and active disturbance rejection control (ADRC) are widely applied, thanks to their high performance and effectiveness in synthesis and realization. However, two knowledge gapsvis-à-visthe dynamical delay and the unification of these techniques exist in literature. This article proposes a study on the unification of DOBC and ADRC for the application of speed control of permanent magnet synchronous motor. The explicit formulas of the estimated disturbance are carried out and the dynamical delays of the observations are, therefore, straightforwardly deduced. By addressing these transparent delay formulas, the unification of DOBC and ADRC is verified. The identical performance of two methods in rejecting both external disturbance and model uncertainty is demonstrated by simulation and experimental validations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".