Connectivity Preservation and Collision Avoidance of Multi-Unmanned Surface Vehicles Via Adaptive Sliding Control
Haobo Kang, Hongjun Ma, Shuai Shao · 2020
This paper investigates the connectivity preservation and collision avoidance problems of a multi-unmanned surface vehicle (USV) system. In order to achieve these two goals more effectively, an improved artificial potential function (APF) is designed. For the sake of solving the issue of nonlinear disturbance, a fuzzy sliding mode control method combined with fuzzy radial basis function neural network (Fuzzy-RBFNN) is introduced. Then by Lyapunov method, it can be proved that the system which employs the control scheme proposed in this paper is stable. In addition, the theoretical deduction proves that the USV can track a given ideal signal, and the connectivity preservation and collision avoidance of the multi-USV system can be achieved during formation. Finally, a multi-USV system model including four USVs is established, and the control strategy designed in this paper is adopted to conduct simulation experiments with MATLAB. The results testify that this control project is valid.