Underwater Glider Motion Control Based on Neural Network
Abstract
Underwater glider is an important equipment for ocean research, water quality detection and other ocean missions. It needs very high precision requirements to meet underwater glider motion control. When the position of buoyancy system changes, the balance parameters will change significantly. This paper presents a method for calculating the balance parameters of underwater glider based on neural network. In order to verify the effectiveness of the neural network control, the South China Sea experiment was carried out. By comparing the analysis results with the actual situation, the experiment shows that the neural network model is feasible.
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