Fast Response Sliding Mode Linear Speed Control of a Magnetic Screw Motor Based on Feedforward Compensation Strategy
Bibliographic record
Abstract
The dynamic performance of the magnetic screw motor (MSM) drive system is influenced by the motor structure. In particular, when the motion direction of the mover changes, the MSM will stagnate for a while. Therefore, a sliding mode linear speed controller (SMLSC) is designed for the MSM linear speed drive system to enhance the dynamic performance of the system. Considering that the regulating function of the controller is limited, a novel feedforward compensation strategy based on the transmission ratio of the MSM is proposed to further shorten the stagnation time of the mover and improve the response speed of the system without affecting the system stability. The proposed compensation strategy can obtain the desired rotor angle speed and the desired$q$-axis current in advance when the given linear speed changes. Then, the desired values are compensated for the given rotor speed and the given$q$-axis current. Furthermore, the influence of the relative motion error caused by the change in transmission ratio on the feedforward compensation strategy is analyzed. The reliability and validity of the proposed method are verified through experiment results.
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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 | 0.000 |
| Open science | 0.001 | 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 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".