Feedback Linearization-Based Position Control of an Electrohydraulic Servo System With Supply Pressure Uncertainty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Electrohydraulic servo systems (EHSS) are used for several engineering applications, and in particular, for efficient handling of heavy loads. proportional-integral-differential (PID) control is used extensively to control EHSS, but the closed-loop performance is limited using this approach, due to the nonlinear dynamics that characterize these systems. Recent studies have shown that feedback linearization is a viable control design technique that addresses the nonlinear dynamics of EHSS; however, it is important to establish the robustness of this method, given that hydraulic system parameters can vary significantly during operation. In this study, we focus on supply pressure variations in a rotational electrohydraulic drive. The supply pressure appears in a square-root term in the system model, and thus, standard adaptive techniques that require uncertain parameters to appear linearly in the system equations, cannot be used. A Lyapunov approach is used to derive an enhanced feedback-linearization-based control law that accounts for supply pressure changes. Simulation results indicate that standard feedback-linearization based control is robust to EHSS parameter variations, providing significant improvement over PID control, and that the performance can be further improved using the proposed control law.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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