An adaptive output feedback formation control algorithm for multiple unmanned surface vehicles based on virtual structure and line-of-sight guidance - Sheng, Luyan; Ye, Hui; Meng, Yizhen; Song, Chengze (Engineering applications of artificial intelligence, 2025)
The formation, and switching control problems for multiple unmanned surface vehicles (USVs) subject to external disturbances and model uncertainties are studied. A novel formation generation algorithm is proposed to address situations where the USV formation needs to rapidly switch its configuration to execute tasks during cooperative navigation. Specifically, an extended virtual structure method is used to generate virtual structure points that enable formation switching. Virtual leaders, based on the artificial potential field method, generate collision-free path-tracking virtual structure points to achieve formation. These virtual leaders provide reference trajectories for the USV’s trajectory guidance. Finally, an adaptive output feedback tracking control method based on line-of-sight (LOS) guidance and neural networks is developed to achieve precise and rapid one-to-one tracking of the virtual leaders by the USVs. The adaptive method compensates for the upper bounds of uncertainties in relative kinematics, and dynamic surface control is used to stabilize the yaw angle tracking error of the following USVs. A high-gain observer is constructed to estimate the speed of the USV, and combining the virtual control law, neural network approximation techniques, and a minimal parameter learning algorithm, an adaptive output feedback tracking controller is designed for the following USVs. The stability of the tracking system is confirmed through Lyapunov analysis. Simulation experiments in MATLAB with varying numbers of USVs and tasks demonstrate the effectiveness of the proposed formation control algorithm. •The algorithm handles disturbances and uncertainties for stable group movement at sea.•A new structure-based method ensures smooth shape changes across tasks and team sizes.•The controller tunes two values for accurate tracking without heavy computation costs.