Buoyancy Regulation Strategy for Underwater Profiler Based on Adaptive Genetic Algorithm

Abstract

Considering the energy limitations of underwater vehicles, a strategy for energy saving is proposed. In the proposed buoyancy regulation strategy, oil of the buoyancy regulation system is pumped out several times at different depths instead of all at once. A balance between energy and time is achieved by assigning suitable weights, and the optimised depth which can be obtained from the pressure sensor is used as the judgement threshold based on the adaptive genetic algorithm. Through the numerical simulation using sea trial data, the influence of weight selection on energy and time is explored, and the frequency of oil draining for the vehicle to ascend is optimised. Simulation results show that the proposed buoyancy regulation strategy can save energy effectively when the frequency of oil draining is 4 times within depths of 0–500 m. Finally, trials were performed in Qiandao Lake and verify the contradictory relationship between energy and time.

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