Bibliographic record
Abstract
This paper describes and compares performances of different fuzzy controllers in stabilizing the balance of an inverted pendulum on a short track after a high disturbance occurs. It compares Mamdani (and its variants, e.g. Passino) with Takagi-Sugeno types of fuzzy controllers and concludes that Takagi-Sugeno is more promising when the length of the track is limited. The work then focuses on the actuator that produces the torque required for the horizontal movements of the inverted pendulum. A control model for the AC motor is used which includes the motor's time constant as the crucial parameter in producing rapid response to the disturbances. Current fuzzy controllers for the inverted pendulum, receive a torque as the input. A disadvantage in this modeling is that the electrical motor dynamics is not built-in in the control system independently. Here, a flux vector control AC electrical motor is incorporated to the system, which receives a voltage as input and produces torque. The new approach in modeling a fuzzy control system assists in 1) selecting sensitive parameters for an optimum high performance electrical motor capable to stabilize the inverted pendulum system and 2) designing a Takagi-Sugeno type fuzzy controller
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".