Frequency Response Identification and Dynamic Modeling of a Magnetic Levitation Device
Bibliographic record
Abstract
Magnetic levitation is an emerging technology in applications such as MEMS production, high speed transportation and biomechanics. Due to the lack of mechanical contact, magnetically levitated devices are unimpeded by problems caused by friction, lubrication and sealing. This paper presents a dynamic model of a magnetic levitation device through the frequency response identification technique. Experimental results verify that the proposed model reasonably matches the actual system’s behavior. The magnetic levitator consists of a set of modules comprising the electromagnets, an iron yoke, a power amplifier, laser position sensors, and a controller. In order to obtain the total transfer function of the system, the dynamic model of each of these modules was obtained individually. The routine presented in this work is remarkable as it leads to the model of a highly nonlinear system through a modular approach that can be applied to a variety of systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".