Adaptive Fuzzy Logic Control of Permanent Magnet Synchronous Machines With Nonlinear Friction
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Bibliographic record
Abstract
In this paper, an adaptive fuzzy control scheme is introduced for permanent magnet synchronous machines (PMSMs). The adaptive control strategy consists of a Lyapunov stability-based fuzzy speed controller that capitalizes on the machine's inverse model to achieve accurate tracking with unknown nonlinear system dynamics. As such, robustness to modeling and parametric uncertainties is achieved. Moreover, no explicit currents loop regulation is needed, which simplifies the control structure and unlike other control strategies, no a priori offline training, weights initialization, parameters knowledge, voltage, or current transducer is required. The system's convergence and stability are proved by Lyapunov stability theory, which yields an improved performance. Simulation results for different situations highlight the performance of the proposed controller in transient, steady-state, and standstill conditions. Furthermore, the adaptive fuzzy systems inherent parallelism makes them a good candidate for implementation in real-time PMSM drive systems.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it