Robust adaptive formation control with autonomous surface vehicles

In this paper, a robust adaptive formation control law is proposed for multiple autonomous surface vehicles moving in a leader-follower formation. The presented method uses only measurements of line-of-sight range and angle by local sensors, no other information about leader is required for control implementation. Neural networks are trained online to compensate for uncertainties due to unknown velocity of the leader. Based on Lyapunov synthesis, the proposed adaptive NN control ensures that both relative distance and angle track the given bounded reference signals to a small neighborhood of zero. The effectiveness of proposed formation controller with applications to three autonomous surface vehicles is illustrated by numerical simulations.