Real-time performance of a nonlinear controller based IM drive
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the real-time performance evaluation of a nonlinear controller for speed control of an induction motor (IM) drive. Neglecting the iron loss in an induction motor model causes performance deterioration. In this work, an adaptive backstepping based nonlinear controller incorporating the iron loss is developed under the parameter uncertainties. The adaptive backstepping technique is utilized to estimate the parameters online and maintain the global stability of the drive. The proposed controller is successfully implemented in real time using a digital signal processor board DS 1104 for a laboratory 1/3 hp IM. Experimental results show that the proposed controller achieves rotor speed tracking objectives successfully and improves dynamic responses as compared to the one without parameter adaptation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 it