New Optimal Control of Permanent Magnet DC Motor for Photovoltaic Wire Feeder Systems
Bibliographic record
Abstract
This article aims to improve the permanent magnet DC (PMDC) motor performance for photovoltaic (PV) wire-feeder systems (PVWFSs) of arc welding machines. The considered technique is designed by direct speed control based on optimal Fractional-order Fuzzy PID FO-Fuzzy-PID controller. The purpose is to ensure optimal control of wire feed speed reference to reduce torque ripples and hence, the performance of the WFS is improved. The dynamic reaction of the proposed solar PVWFS relies upon the scaling factors of FO-Fuzzy-PID controller, which are optimized by using teaching-learning algorithm based on Particle Swarm Optimization (PSO) method. The maximum power point tracking (MPPT) is achieved using an intelligent FO-Fuzzy-PID current controller based Perturb and Observe (P&O) MPPT algorithm. The PVWFS system incorporating the proposed method is tested and compared with the conventional PID control scheme under different weather conditions. The simulation of the proposed system by MATLAB\SIMULINK is carried out. The simulation results indicate the effectiveness of the considered control strategy in terms of the reduction in torque oscillations, optimizing electrical power and wire feed speed.
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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) | 0.001 | 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".