Collaborative Path Tracking Control Method of USV Cluster Based on RBF Integral Sliding Mode

To meet the requirements of ship escorts and target enclosure, a collaborative path tracking control method for underactuated unmanned surface vessel(USV) cluster based on a path parameter cycle is proposed in this study. In a kinematics design that includes line-of-sight guidance and a consistency algorithm, a collaborative guidance law is designed for the USV cluster. This design realizes symmetrical formation on a closed curve and target enclosure. In a dynamics design in which model uncertainties and chattering induced by the traditional sliding mode are considered, a distributed integral sliding mode controller based on an adaptive radial basis function neural network is designed. This distributed integral sliding mode controller uses the approximation characteristics of the neural network and the saturation function to ensure that the USV can track guidance signals accurately, thereby improving the anti-interference of the system and path tracking accuracy. The study also conducts a Lyapunov stability analysis to show that the errors of the closed-loop system are globally asymptotically stable. Simulation results reveal the effectiveness of the proposed collaborative path tracking control method.