Design close-loop control of BLDC motor speed using PID method in solar power with matlab/simulink
Bibliographic record
Abstract
In this research, the design of close loop BLDC motor speed control was designed with several simulation test conditions and also discuss the differences of boost converter with Fuzzy control and boost converter without Fuzzy control. The BLDC motor specifications used in this research are 3 phase, constant voltage is 80 V_peak L-L / krpm and the moment of inertia is 0.000553 J (kgm2). The specifications of the solar were Canadian CS5T 130M with a maximum power=129W. The test results on the boost converter without using Fuzzy controls have fluctuating voltages. Whereas when using PID controls, the output voltage is stable and the voltage is±100 V. In simulation, PID control circuits have THD values amounting to 3.12%, which corresponds to the standards specified by IEEE for voltages below 1 kV=<5%. The simulation test results with several conditions have made a difference in the results of the motor speed response. Based on the results of the simulation test, it is known that the speed control with the PID control circuit has better results compared to the open loop circuit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".