Optimal Fractional Order Proportional Integral Controller for Dual Star Induction Motor Based on Particle Swarm Optimization Algorithm
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Bibliographic record
Abstract
The purpose of this paper is to improve the performance of the conventional direct torque control (DTC) method of a dual star induction motor (DSIM) by enhancing speed control and reducing the ripples of electromagnetic torque and stator current.To achieve this, we propose a new optimal tuned controller based on the combination of a fractional order proportional integral controller (FOPI) and particle swarm optimization (PSO) algorithm.The aim of this high-performance controller is to reduce the rise time, settling time, steadystate error, and effects of load disturbances in the speed response of the DSIM, as well as minimize oscillations in the torque and stator currents, particularly at low speeds.This strategy named DTC-FOPI-PSO will be investigated, and its performances will be compared with the traditional DTC strategy based on the classical PI controller.Simulation tests using MATLAB/Simulink software are conducted under different operating conditions to demonstrate that the proposed DTC-FOPI-PSO strategy has a direct impact on improving speed dynamic, reducing torque fluctuations, minimizing steady-state error and provides excellent performance for load variation and reference speed inversion.
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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 | 0.001 |
| 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)
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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