Time Delay Estimation Based Discrete-Time Super-Twisting Current Control for a Six-Phase Induction Motor
Bibliographic record
Abstract
This article tackles the problem of high-accurate tracking of the stator currents of a six-phase induction motor in the presence of unknown dynamics such as unmeasurable rotor currents, parameter variation, and disturbances. Since the good features offered by sliding mode theory motivate the community of researchers on control, a time delay estimation based discrete-time super-twisting controller is proposed. First of all, an outer loop is carried out to regulate the speed and to generate the desired stator currents. Second, the inner loop, based on an indirect rotor field-oriented control, is executed based on the developed approach. The structure of the proposed method allows a precise approximation of the unknown dynamics and an accurate tracking and a fast convergence of the tracking error to a neighbor of zero. The design procedure and the stability analysis are detailed for the stator currents closed-loop system. Experimental tests have been performed on a six-phase induction motor to demonstrate the effectiveness of the developed discrete approach. In addition, the performances obtained are compared to the ones obtained using the discrete-time sliding mode with time delay estimation. The results obtained highlighted the satisfactory stator currents tracking performance in transient conditions and steady state and under different sampling times, parameters mismatch, and load and no-load conditions.
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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".