Variable universe fuzzy control of the wheel loader semi-active cab suspension with multimode switching shock absorber
Bibliographic record
Abstract
The aim of this work is to design a variable universe fuzzy control of a wheel loader semi-active cab suspension with damping multimode switching shock absorber. Considering the cost and reliability, a new type of shock absorber, whose adjustable damping characteristics are achieved by just changing the on–off statuses of two solenoid valves, is applied to the wheel loader cab suspension. The vibration model of the wheel loader, which considers the vibration characteristics of the working device, the four-wheel correlated random road excitation, and the engine vibration excitation simultaneously, is established first. Based on the working principle of the target shock absorber, the damping multi-state switching model is also established to reflect the relationship between the damping coefficients and the on–off statuses of two solenoid valves. Then, a variable universe fuzzy damping control strategy, which can determine the optimal switching sequences of the damping modes according to the cab suspension performance indexes, is designed. Finally, simulation analyses were conducted to verify the effectiveness of the proposed control approach of the wheel loader semi-active cab suspension with multimode switching shock absorber.
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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) | 0.001 | 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 | 0.000 | 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".