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Outline
During maritime operations, ships are subject to wave-induced disturbances, resulting in complex multi-degree-of-freedom motions that severely affect the stability of ships during offshore operations. To address this challenge, this study proposes a CNN-BiLSTM hybrid prediction model for real-time ship attitude forecasting and designs a dual-layer Stewart platform compensation mechanism to mitigate ship motion effects. To overcome sensor latency and noise interference, 2011 ship attitude samples collected in the South China Sea were first filtered using a Savitzky-Golay (SG) filter. The processed data were then fed into the CNN-BiLSTM hybrid prediction model, which significantly improved the accuracy of attitude prediction. Furthermore, a platform kinematic model was established using the closed-loop vector method. The predicted data were utilized to compensate the dual-layer Stewart platform, enabling coordinated control between the lower platform (simulating wave disturbances) and the upper platform (performing dynamic compensation). Experimental results demonstrate that the proposed approach achieves effective ship attitude compensation and provides a feasible solution for stable landing operations of unmanned aerial vehicles (UAVs) at sea.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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