Experimental Investigation on Swash Plate Axial Piston Pumps With Conical Cylinder Blocks Using Fuzzy Logic Control
Bibliographic record
Abstract
Analytical studies on the dynamic performance of variable displacement swash plate axial piston pumps show that the pump performance can significantly improved by replacing the conventional PD process controller with fuzzy logic controller. Electrically controlled, constant power regulated, swash plate pumps with conical cylinder blocks have been recently extensively studied. Comparative study has been carried out to compare the pump dynamic performance when the conventional PD process controller is replaced by a proposed fuzzy logic one. The study reveals some superior performance characteristics when fuzzy logic controller is used. In the present study an experimental setup is built to measure the dynamic performance of a typical 9-piston pump that has conical shaped cylinder block. The pump is of 40 cc/rev geometrical size, type A4VSO, that is manufactured by Rexroth. The experimental setup consists of a hydraulic test bed interfaced with real time control and data acquisition system. The setup is used firstly for testing the pump static characteristics. Subsequently, the setup is used to measure the time response of the pump, which is equipped with the conventional PD controller, to the stepwise changes in the load pressure. Pump model verification is then discussed based on the comparison between the theoretical and experimental results. The pump is afterwards interfaced with real time control software for prototyping the proposed fuzzy logic controller that replaces the currently used PD one. With the fuzzy logic control, measuring the pump time response under the same loading conditions is repeated. Experimental results are presented, compared with the analytical findings and discussed.
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 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) | 0.001 | 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 teacher head, 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".