Control parameter optimization of underwater gliders for turbulence observation

Abstract

Turbulent mixing plays an important role in shaping the circulation and distribution of heat and carbon within the climate system. Underwater gliders are ideal turbulence observation platforms, but appropriate control parameters are required for them to achieve high-precision and large-scale continuous turbulence measurement, for which speed and endurance are two important indicators. Taking these indicators as the optimization objectives, this study establishes an optimization model for the control parameters of underwater gliders, which integrates two gliding strategy models, a dynamic model, and an energy consumption model. The multi-objective optimization of both conventional gliding strategy and our pitch adjustment strategy is performed with non-dominated sorting genetic algorithm-II to obtain the optimal control parameters. After the optimization, both gliding strategies can achieve an ideal gliding speed for turbulence observation, with the gliding range increased by more than 6% in the diving phase and more than 10% in the climbing phase. The proposed optimization model is verified to be effective with a sea trial performed by Petrel-L underwater glider. After proper modifications, the proposed method is expected to be further applied to other types of gliders.