Fixed-Time Adaptive Chaotic Control for Permanent Magnet Synchronous Motor Subject to Unknown Parameters and Perturbations
Bibliographic record
Abstract
It is well known that the permanent magnet synchronous motor (PMSM) exhibits chaotic characteristics when its parameters fall within a certain range, which can lead to system instability. This article proposes an adaptive control strategy for achieving the fixed-time chaotic stabilization of PMSM, even in the presence of unknown parameters and perturbations. The developed controller is synthesized by combining a parametric adaptive mechanism with a fixed-time control technique. The stability analysis demonstrates that the system states under the developed controller can converge to small neighborhoods around the equilibrium point within a fixed time. Thanks to the adoption of the parametric adaptive mechanism, the developed controller is not only insensitive to unknown parameters but also robust against perturbations. Finally, simulated studies are conducted to verify and emphasize the effectiveness of the developed control strategy.
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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 | 0.000 | 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 | 0.000 |
| 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".