| 摘要 |
A method of generating a model of propulsive efficiency for an autonomous underwater vehicle (AUV) is based on a multilayer perception neural network model using data from aquatic species, such as undulatory fin propulsion in the knifefish (Xenomystus nigri), and a sensitivity analysis is used to lower the number of required inputs. The model of propulsive efficiency allows an AUV to achieve high values of propulsive efficiency over a range of forward velocity, giving a lowered energy drain on the battery. In an embodiment, externally monitored information, such as that on flow velocity, is conveyed to an apparatus residing in the vehicle's control unit, which in turn signals the locomotive unit to adopt kinematics, such as fin frequency and amplitude, associated with optimal propulsion efficiency. Power savings could protract vehicle operational life and/or provide more power to other functions, such as communications. |
