Cross-axis coupling suppression method based on TITO-SGPC for active magnetic compensation system
Bibliographic record
Abstract
Abstract This study addresses the challenge of cross-axis magnetic field coupling in active magnetic compensation (AMC) system for magnetic shielding room (MSR), which limits control accuracy in weak magnetic environment. A three-input three-output (TITO) model of AMC system is constructed, and a simplified generalized predictive control (TITO-SGPC) is proposed, using attenuation sequence to reduce high-dimensional matrix operations. Experimental results show that TITO-SGPC suppresses cross-axis coupling magnetic field within 0.34 nT, achieving over 2.4 times higher suppression than traditional GPC. Compared with multiple-input multiple-output model predictive control (MIMO-MPC), the computational complexity is significantly reduced, the execution time and memory usage are reduced by 14 times and 2.2 times, respectively, and it has better disturbance suppression effect. This method overcomes the limitations of traditional decentralized control and computationally intensive MIMO methods by explicitly establishing a three-axis cross model, and uniquely balances coupling suppression and real-time performance. This study provides a modular and high-precision solution for biomagnetic measurement, enabling stable control in MSRs with different geometries and supporting advancements in weak magnetic measurement technology.
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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 | 0.001 |
| 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".