REAL-TIME VELOCITY AND DIRECTION ANGLE CONTROL OF AN AUTOMATED GUIDED VEHICLE
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Bibliographic record
Abstract
In this paper, an adaptive fuzzy control (AFC) system is applied to velocity and direction angle control of a certain type of wheeled mobile robots called automated guided vehicles (AGVs). The fuzzy control system includes an adaptive model identifier and controller. The gains of fuzzy controller are obtained by using the fuzzy identifier model which is defined by real system outputs and control inputs. The parameters of fuzzy identifier model are adjusted online by using recursive least square algorithm. A PI controller is also applied to AGV to show the robustness of the AFC system. Experimental results prove that the AFC shows better tracking performance than the PI controller in terms of robustness, smoothness and fast dynamics. Results are given for complex references, sudden disturbance and extra load conditions.
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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 | 0.000 |
| 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 it