Force Ripple Attenuation of 6-DOF Direct Drive Permanent Magnet Planar Levitating Synchronous Motors
Bibliographic record
Abstract
A novel direct drive 6-degree-of-freedom (DOF) planar levitating synchronous motor has been developed that is comprised of multiple 1-D magnet arrays attached to a moving stage and multiple stationary 1-D coils built as a printed circuit board (https://www.youtube.com/watch?v=-r4Tv7GbB8o). Together these make up a set of four 2-DOF Lorentz force motors that actuate the moving stage in 6-DOF over a large planar range. This motor topology allows scalability with minimal increase in controller and drive complexity as well as direct drive actuation of a single mover body without intervening bearing elements, making it ideal for a variety of industrial automation and manufacturing applications. For high performance applications that require rapid high-precision motion, a linear, position independent force characteristic is desired to minimize the controller effort and reduce the intrinsic force disturbances, which adversely affect positioning accuracy. In the presented planar levitating synchronous motor, the primary source of force disturbance is the interaction between higher order spatial harmonics of the magnetic field of the mover and the commutated excitation current in the stationary coils. This paper presents analysis and experiment results of a novel method of reducing force ripple associated with permanent magnet planar levitating synchronous motors through the design of appropriately split and spaced magnet arrays. This method internally cancels out specific force harmonics within each 2-DOF motor, without adding controller complexity or resorting to higher order magnet arrays. Experimental results demonstrate force ripple reduction from 1.1% without magnet array splitting to 0.12% with magnet array splitting.
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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) | 0.000 | 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 | 0.000 |
| 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".