Bibliographic record
Abstract
This paper deals with the development of a nonlinear control strategy for asymmetric actuators. In asymmetric actuators, the generated force/torque is not symmetric in push and pull. Examples of asymmetric actuators are thrusters, shape memory alloy wires, and in general, cables and long rods that cannot be used for compression forces. These actuators are called unidirectional. More complex asymmetric actuators are those that generate uneven push and pull forces. Examples of these actuators are double acting hydraulic and pneumatic cylinders in which the area of the piston is not the same in forward and reverse directions. Since in the existing control techniques the actuator is assumed to be symmetric, the application of asymmetric actuators requires new control schemes. In this paper, we propose a nonlinear control method capable of producing any biased input that can be used by asymmetric actuators. The controller is based on quadratic coupling terms with which positive, negative, and any biased input can be generated. We study the stability of the system along with a method to select the controller gains for tuning the output of the controller to match the actuator type. The normal form method and perturbation techniques are used to study the controller design.
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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".