Design and Control of the Angular Acceleration of a Hydraulic Rotary Actuator to Simulate a Flexible Joint Robot
Bibliographic record
Abstract
The objective of this work was to design and implement an experimental hydraulic system that simulates joint flexibility with the ability of changing the joint flexibility's parameters. Such a system could facilitate future control studies by reducing investigation time and implementation cost of research. It could also be used to test the performance of different strategies to control the movement of flexible joint manipulators. A hydraulic rotary servo actuator was used to simulate the action of a flexible joint robot manipulator. A challenging task since the control of angular acceleration was required. A single-rigid-link, elastic-joint robot manipulator was modeled using Matlab®. Joint flexibility parameters such as stiffness and damping, could be easily changed. This simulation could be referred to as "function generator" to drive the hydraulic flexible joint robot. In this study the angular acceleration was used as the input to the hydraulic rotary actuator and the objective was to make the hydraulic system follow the desired acceleration in the frequency range specified. The hydraulic system consisted of a servo valve and rotary actuator. A hydraulic actuator robot was built and tested. The results indicate that if the input signal had a frequency in the range of 5 to 15 Hz and damping ratio of 0.1, the experimental setup was able to reproduce the input signal with acceptable accuracy. Because of the inherent noise associated with the measurement of acceleration and some severe nonlinearities in the rotary actuator, control of the experimental test system using classical methods was not as successful as had been anticipated. This was a first stage in a series of studies and the results provide insight for the future application of more sophisticated control schemes.
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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".