Adaptive fuzzy variable structure control of induction motors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In variable structure sliding mode control schemes, one has to adjust the controller gains in order to obtain an acceptable response. The controller gains are required to be readjusted under variation of the disturbance load torque and/or of the parameters of the induction motor. To compensate automatically for the uncertainties experienced by the system, the controller gains are adjusted by a fuzzy inference mechanism. Furthermore, an adaptive fuzzy sliding mode controller is proposed. It combines the merits of sliding mode control, fuzzy inference mechanism and the adaptive algorithm. First, a sliding mode controller is designed, and then a fuzzy inference mechanism is used to compensate for the uncertainties experienced by the system by adjusting the reaching rates of the sliding mode controller. Finally an adaptation algorithm is used to adjust the centers of the fuzzy sets in order to reduce the control effort and chattering. Simulation results verify the effectiveness of the proposed algorithm.
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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 | 0.000 |
| 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 it