Autonomous Underwater Vehicle (AUV) is widely used for observations in polar regions. In order to maintain a stable observation state, the horizontal hovering control of AUVs has become a research topic of interest. Effective horizontal hover control can reduce underwater noise, save energy and extend the duration of experiments. In this paper, a control strategy for AUV hovering was designed using a X-rudder vehicle with vertical thrusters as the experimental platform. Hover-style and Flight-style control strategy are introduced, optimized for hovering states and navigational movement, respectively. Notably, considering the over-actuated system of the TS-100, precise control allocation for the actuators is implemented based on a sequential quadratic programming (SQP) algorithm. Finally, experimental results in a water tank validated the effectiveness of the control algorithm. Compared to CA not used, this control strategy reduces the hovering range, suppresses roll motion, and allows for faster adjustments. This method has practical applications in polar underwater observations, allowing better tracking of stationary observation for extended periods.
Until now, the polar regions remain the least explored parts of the Earth's oceanic regions, despite their key role in the process of climate change (Bootz, Lievre, and Schenk 2015). Over the past decade, AUVs have rapidly become the preferred platform for observing the underside of sea ice and conducting geological and biological oceanographic measurements in the Arctic and Antarctic (Singh et al. 2017). AUVs have changed resolution of seafloor imaging, particularly in their role in exploring extreme environments, which is now undeniable (Sahoo, Dwivedy, and Robi 2019). The application of AUVs in marine geology is becoming increasingly diverse (HUANG Yan et al. 2020)). In the polar regions, AUVs have begun to be used for a variety of tasks, including detecting the characteristics of low-temperature fluid seepage, mapping benthic habitats in both deep and shallow water environments, and mapping morphological features of the seabed(Wynn et al. 2014).