LAUSR

This article mainly researches the problem of distributed finite-time coordinated path-following for under-actuated autonomous surface vehicles (ASVs) within a network swarm. Each vehicle in swarm system suffers from velocity restrictions and multiple uncertainties including parameter perturbations and time-varying environment disturbances. Based on the constructed bionic swarm pattern and potential function, the swarm velocity guidance (SVG) with self-organization and collision avoidance is developed to guide ASV surge velocities and heading angles simultaneously. A distributed observer by adding correction terms to the vehicle model is involved to identify the lumped uncertainties, and the estimations are utilized as feed-forward compensation to weaken the uncertainty impact, thus achieving high tracking precision. By using asymmetric barrier Lyapunov function, the uncertainty observer based distributed surge and heading kinetics controllers under physical restrictions are devised to guarantee that the guided signals generated by SVG are tracked within finite time. Through simulation studies of swarm path-following, it is demonstrated that the designed control approach is feasible and efficient for multiple uncertain under-actuated ASVs.