IDENTIFICATION OF THE NONLINEAR FRICTION CHARACTERISTICS IN A HYDRAULIC ACTUATOR USING THE EXTENDED KALMAN FILTER
Bibliographic record
Abstract
In this paper, the nonlinear friction characteristic of a custom made symmetrical linear hydraulic actuator is investigated using the Extended Kalman Filter (EKF). A new and very accurate characterization of friction is made by using a quadratic function of the piston velocity. Further to this proposed empirical friction model, the EKF is used to estimate the function coefficients. In this paper, an iterative approach is used to maintain system observability and render the estimation process more reliable. The study is conducted in simulation and by using measured experimental data. The estimated states and parameters by the EKF are found to be convergent to their known values in simulation and, further to experimental results, unique and repeatable. In addition, changes in the friction characteristics, which can occur in the physical system due to wear in the piston seals or degradation in the oil properties, are detected and accurately estimated by the EKF in simulation. This study presents an accurate nonlinear model for the representation of friction in a hydraulic actuator. It paves the way for the implementation of strategies for early fault detection in hydraulic systems.
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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) | 0.000 | 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 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".