A Novel Control Strategy for Online Harmonic Compensation in Parametrically Unbalanced Induction Motor
Bibliographic record
Abstract
Inverter-fed motor drive operating an unbalanced induction motor (IM) has high harmonic content which inflicts large torque ripple on the load. Dead short circuit and incipient or partial short circuit in motor stator windings lead to asymmetry in the machine parameters. Consequently, an imbalance in the voltage supply worsens the condition deteriorating the optimal performance of the drive-based motor due to the injection of both increased time and spatial harmonics. It is of primary importance that these discrepancies are taken care of while modeling a more fault tolerant, reduced harmonics drive system. This paper proposes a novel control strategy to minimize torque ripple by considering the time harmonics produced due to imbalance in inverter voltage and parameters of the faulty IM, and the estimated space harmonics from the measured magnetic flux density in a transient magnetic phenomenon. The proposed control strategy has been implemented on an unbalanced aluminum-rotor IM with online monitoring of unhealthy conditions and feeding it to the harmonic compensation block of the drive system.
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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".