Research on Dynamic Positioning Methods of Unmanned Surface Vehicles Applied to Algae Removal

Excessive proliferation of algal organisms can severely affect water quality and ecological security. Traditional algae removal techniques, including physical, chemical and biological methods, generally exhibit shortcomings such as long algae removal cycles and impact on water quality, and they cannot meet the algae removal needs of large-scale flowing water areas in the South-to-North Water Diversion Project (SNWDP). This study addresses the key technical challenges in algae removal operations on the slopes of the SNWDP, and an integrated algae removal solution based on an unmanned surface vehicle (USV) platform is proposed. This solution offers advantages such as high automation, notable adaptability, efficient algae removal, and minimal impacts on water quality. To mitigate environmental disturbances caused by wind, waves and currents, and enhance the accuracy and efficiency of USV operation, a dynamic model of a USV as a controlled object is first established, and an adaptive backstepping sliding mode control (ABSMC) algorithm for its dynamic positioning is proposed. Through numerical simulation and comparative analysis under different conditions, the effectiveness of the designed control algorithm is validated, and key parameters are optimized. The proposed control algorithm facilitates fast and accurate dynamic positioning and trajectory tracking, thereby enhancing the precision and efficiency of the USV platform in algae removal operations.