Evaluation of Both Linear and Non-Linear Control Strategies for a Shipboard Marine Gantry Crane
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Bibliographic record
Abstract
Anti-sway control for shipboard marine cranes is an ongoing control problem. In this paper, a simulation tool was developed to evaluate anti-sway controllers for a five degree-of-freedom shipboard gantry crane, actuated as if at sea. The simulator was developed in MATLAB Simulink and ran in real-time with controllers operating on a National Instruments myRIO. A proportional-integral-derivative controller (PID), a model predictive controller (MPC), a sliding mode controller (SMC) and a fuzzy logic controller (FLC) were developed to track a desired trajectory and dampen out payload sway. The controllers were tested both individually and with input commands shaped by a zero-vibration (ZV), zero-vibration-derivative (ZVD) and zero-vibration-derivative-derivative (ZVDD) input shaper. The PID, SMC and FLC controllers were all capable of both tracking the desired trajectory and dampening payload sway without disturbances from ship motion, with the more complex FLC and SMC showing little improvement over the simpler PID. The MPC was unable to track the desired trajectory without jumping the actuator deadbands. The addition of input shapers provided a greater reduction in payload sway at the cost of a delayed response, with the ZVDD showing the greatest reduction in payload sway and the corresponding longest delay. Given the length of the delays however, it is recommended input shaping only be applied to automated or autonomous crane systems. As designed, none of the controllers were able to successfully track the desired trajectory in the presence of ship motion. With the simulation tool, future work for this system will involve improving the control response to ship motion disturbances, operator-in-the-loop testing and hardware deployment.
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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 | 0.001 | 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 it