Fractional-Order Sliding Mode Terrain-Tracking Control of Autonomous Underwater Vehicle with Sparse Identification

This paper has addressed the terrain-following problem of an autonomous underwater vehicle for widely used ocean survey missions. Considering the terrain feature description with limited sensing ability in underwater scenarios, a vertically installed multi-beam sonar and a downward single-beam echo sounder are equipped to obtain seafloor detecting data online, and a local polynomial fitting algorithm is carried out with a receding horizon strategy in order to generate a proper tracking path to keep the desired height above the sea bottom. With the construction of the autonomous underwater vehicle dynamic model in the North East Down frame regarding the vertical plane, an online sparse identification algorithm is implemented to obtain the model parameters during the diving process. Then, a fractional-order sliding mode controller is proposed to enable accurate tracking of the path planned and Lyapunov-based theory is utilized to prove the stability of the control algorithm. With the simulation results, the tracking effectiveness of the fractional-order sliding mode controller with in situ identification is verified.