Design of a Novel Fuzzy Controller to Enhance Stability of Vehicles
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the design of a novel fuzzy control structure to improve stability of vehicles with semi-active suspension system. The proposed fuzzy controller adjusts the damping coefficient to stabilize the sprung mass and hence reduce the tendency of vehicle to rollover. A full car model with eight degrees of freedom is adopted that includes the vertical, roll, yaw, and pitch motions as well as the vertical motions of each wheel. Four decentralized fuzzy controllers are developed and applied to each individual damper in the vehicle suspension system. The controllers input(s) are lateral acceleration and vehicle states and the output is an adaptive damping coefficient. Mamdani's inference engine is used to obtain the required damping coefficient of each suspension system. To evaluate the performance of the proposed controller, experiments were performed for simple turn and lane change maneuvers. To show the effectiveness of the proposed controller, comparison is made with Cadillac controller. Results show that the fuzzy controller reduces roll angle, linear transfer ration (LTR) and hence decreases the propensity to rollover in vehicles.
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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 | 0.001 | 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