Research on the Thrust Allocation Method for Straight-Line Sailing of Multiple AUVs in Tandem Connection - Jin Zhang; Shengfan Zhu; Shuai Kang (Applied Sciences)
The relative motion and coupled dynamics between individual units in a Multiple AUVs in Tandem Connection (MATC) system make speed and inter-unit distance control particularly challenging, especially in large-scale configurations. This study proposes a novel hybrid thrust allocation method for steady straight-line sailing in MATC systems, addressing thrust constraints and unit coordination. First, the motion model of the MATC system was established based on Newton’s second law. Second, an improved Genetic Algorithm (GA) was developed to optimize thrust values for each unit in smaller configurations. Third, to address the computational challenges of thrust allocation in large MATC systems, an offline model training method was introduced, combining the Harris Hawks Optimization (HHO) algorithm with a BP neural network. Simulations were conducted for MATC configurations with 5 and 30 AUV units. The results demonstrate that, under current disturbances, the inter-unit distances and overall speed for the 5-unit MATC system quickly converged to target values of 0.12 m and 1.5 knots, respectively, without exceeding the 3.5 N thrust constraint. For the 30-unit MATC system, the proposed method achieved rapid convergence to target values, with a 56% reduction in straight-line speed deviation compared to using the improved GA alone. These findings validate the effectiveness of the proposed approach in enhancing control accuracy and scalability in MATC systems, offering significant potential for large-scale underwater applications.