Real-time computation-efficient formulation for speed-sensorless drive of induction motors
Bibliographic record
Abstract
Induction motors are the workhorse of our industries, continuously applied in new areas with improved performance utilizing modern power electronics and digital controls. This paper proposes a new computationally efficient real-time control for induction motor drives using state-of-the-art digital signal processing (DSP) technology, but without using a speed sensor. This control is named Advanced Speed-sensorless Induction-motor Drive (ASID). Its advantages are particularly evident in hostile application environments where maintenance of speed sensors requires costly downtime or their installation is physically difficult. This paper details ASID control algorithms, formulations, and implementations. The features of the ASID are demonstrated and compared with the manufacturer-recommended speed-sensorless drive control. Key comparisons provided in the paper include efficiency of computations, easy of real-time implementations, simplicity of control algorithms, accuracy of speed estimations, convergence and stability of feedback controls, comprehension of control methodology, etc.
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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".