Back-Stepping Formation Control of Unmanned Surface Vehicles With Input Saturation Based on Adaptive Super-Twisting Algorithm
Yuhan Zou, Kun Wang, Wei Shang, Zhou Liu, Zhongzhong Zheng, Jing Guo Hao
Abstract
Aiming at the formation control problem for unmanned surface vehicles under input overload and external disturbance, a leader-follower formation control law based on input saturation and the adaptive super-twisting algorithm was designed in this paper. Firstly, the mathematical model of underactuated unmanned surface vehicle formation based on the leader-follower method is established, and the virtual expected velocity is designed by the back-stepping method to improve the control accuracy of formation. Secondly, the parametric uncertainties and unknown external disturbances in the USV’s dynamical model are compensated by the proposed adaptive super-twisting control laws. In addition, the input saturation function is added to the controller to avoid machine necrosis caused by input overload. Finally, Simulation results show that the controller can roughly keep the trajectory of the USV consistent with the expected trajectory and ensure that the input values are within the safe range, which proves the effectiveness of the method in this paper.