This paper investigates the formation keeping problem of heterogeneous ships with underactuated inputs, uncertain dynamics, and environmental disturbances. The control objective is to make the heterogeneous followers keep the desired formation while tracking a leader. To solve the problem effectively, a novel virtual leader–follower formation scheme considering the ship heterogeneity is proposed by utilizing the backstepping method, adaptive neural network, and adaptive control law. The stability of the formation control system is proved based on Lyapunov's direct method where all tracking errors are guaranteed to be uniformly ultimately bounded. Finally, simulations and comparisons are conducted to verify the effectiveness of the proposed control law.

The future autonomous ships will be operating in an environment where different autonomous and non-autonomous vessels with different characteristics exist. These vessels are owned by different parties and each uses its owned unique approaches for guidance and navigation. The Collaborative Autonomous Shipping Experiment (CASE) aims at emulating such an environment and also stimulating the move of automatic ship control algorithms towards practice by bringing together different institutes researching on autonomous vessels under an umbrella to experiment with collective sailing in inland waterways. In this paper, the experiments of CASE 2020 are explained, the characteristics of different participating vessels are discussed and some of the control and perception algorithms that are planned to be used at CASE 2020 are presented. CASE 2020 will be held in parallel to iSCSS 2020 at Delft University of Technology, the Netherlands.