Feedback Control of a Two-Degree-of-Freedom Electromagnetic Reluctance Precision Motion System
Bibliographic record
Abstract
This study investigates a novel Xθ actuation system driven by a reluctance actuator (RA) and two accompanying moving magnet actuators (MMAs). The system enables precise control of both translational (x) and rotational (θ) motion, offering a two-degree-of-freedom (2DOF) solution for high-precision applications. The two MMAs introduce additional force and torque dynamics through the solenoid and permanent magnet (PM) pairs. Flexure hinges assist with the retraction force of the mover element, providing the necessary stiffness without introducing frictional effects. The system was modeled analytically, optimized, and validated experimentally with a developed feedback and feedback control, achieving steady-state errors of approximately ±7 µm in x translation and ±0.3 mrad in θ rotation which can be attributed to systematic errors in the sensor itself. The most relevant application is the fastscan mirror in extreme ultraviolet (EUV) lithography where specific targeted rotational and translational trajectories can benefit light beam positioning, such as wavefront corrections. This system allows translation and rotation specifications to be realized in one actuation unit, opening up more design possibilities for controlling precision motion systems.
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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 | 0.000 |
| 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 | 0.001 | 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".